IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
A multi stage heuristic for manufacturing cell formation eSAT Journals
This document presents a multi-stage heuristic for solving the manufacturing cell formation problem. The heuristic first uses a two-stage cluster analysis approach to initially group machines and assign parts, aiming to maximize grouping efficacy measures. This initial solution is then improved using a simulated annealing technique. The heuristic is tested on both binary and non-binary datasets, and results indicate it generates promising quality solutions compared to other cell formation approaches.
This document presents a new approach for forming part families and machine cells in a batch-oriented production system. The approach combines a local search heuristic with a genetic algorithm. The genetic algorithm is used to generate initial machine cell sets, while the local search heuristic considers both inter-cell movement and machine utilization to improve the groupings. The heuristic feeds back grouping efficacy results to the genetic algorithm until an optimal solution is found. The goal is to maximize grouping quality and machine utilization within cells, while minimizing inter-cell movement of parts. The approach is tested on a sample manufacturing data set, with results showing higher grouping efficacy than traditional methods.
A New Mathematical Model for Minimization of Exceptional Load in Cellular Man...IJRES Journal
This study is devoted to the cell formation problems in cellular manufacturing systems. Starting point of this study is a paper of Mahdavi et.al. which considers only a few factors of production system. In this research, processing times and the frequencies of the parts are also considered. It is assumed that the load of each machine is known and is the multiplication of the processing times and frequencies. In this case cells are formed to achieve the higher loads inside cells. Also, the proposed model is about the case when alternative technologies are available and the objective is to maximize the loads inside cells. Besides the new model, other main contribution of this study is the computational analysis. The results show that the new model is providing acceptable solution within the logical runtimes.
This document presents a stochastic extension of a cellular manufacturing system model that considers uncertain arrival rates and service times. The model is formulated as a queueing system and aims to minimize the sum of machine idleness costs, subcontracting costs, non-utilization costs, and holding costs. It introduces a chance constraint to ensure the probability that the average waiting time exceeds a critical time is below a service level. The arrival and service rates are modeled with exponential distributions. The model will be solved using GAMS software and sensitivity analysis will examine the impact of parameter changes.
Survey on Segmentation of Partially Overlapping ObjectsIRJET Journal
This document summarizes several existing methods for segmenting partially overlapping objects in digital images. It discusses challenges in segmenting overlapping objects and different approaches researchers have used, including watershed-based methods, graph cuts algorithms, active shape models, and level set methods. The goal of segmentation is to partition an image into meaningful regions to analyze objects and boundaries. Efficient segmentation of overlapping objects remains an important challenge in image processing.
ENHANCED BREAST CANCER RECOGNITION BASED ON ROTATION FOREST FEATURE SELECTIO...cscpconf
Optimization problems are dominantly being solved using Computational Intelligence. One of
the issues that can be addressed in this context is problems related to attribute subset selection
evaluation. This paper presents a computational intelligence technique for solving the
optimization problem using a proposed model called Modified Genetic Search Algorithms
(MGSA) that avoids local bad search space with merit and scaled fitness variables, detecting
and deleting bad candidate chromosomes, thereby reducing the number of individual
chromosomes from search space and subsequent iterations in next generations. This paper aims
to show that Rotation forest ensembles are useful in the feature selection method. The base
classifier is multinomial logistic regression method integrated with Haar wavelets as projection
filter and reproducing the ranks of each features with 10 fold cross validation method. It also
discusses the main findings and concludes with promising result of the proposed model. It
explores the combination of MGSA for optimization with Naïve Bayes classification. The result
obtained using proposed model MGSA is validated mathematically using Principal Component
Analysis. The goal is to improve the accuracy and quality of diagnosis of Breast cancer disease
with robust machine learning algorithms. As compared to other works in literature survey,
experimental results achieved in this paper show better results with statistical inferenc
A Hierarchical Clustering Algorithm Based Computer Aided Molecular Modeling w...IOSR Journals
This document presents a novel hierarchical clustering algorithm for color image segmentation of Haematoxylin and Eosin (H&E) stained images of colon cancer. The algorithm aims to classify differences between benign and malignant tumor cells. It involves reading an input color image, coarse representation using 25 bins, hierarchical clustering to segment the image into classes, and outputting the segmented image. Intermediate steps include filtering, normalization, and segmentation of nuclei into a separate image in MATLAB for real-time simulation. Results show the algorithm improves color segmentation accuracy over previous k-means clustering approaches and provides features for region of interest classification of benign and malignant tissues.
This document proposes a method to detect diseases in tree leaves and fruits using convolutional neural networks. The method involves preprocessing images by resizing and converting them to grayscale. Noise is removed using median filtering. Images are then segmented and features are extracted. A convolutional neural network is trained on labeled image features and used to classify new images and detect diseases. Results on test images show the preprocessing steps and segmentation being applied before classification with CNN. The method is presented as an effective way to accurately detect diseases at early stages for successful agriculture.
A multi stage heuristic for manufacturing cell formation eSAT Journals
This document presents a multi-stage heuristic for solving the manufacturing cell formation problem. The heuristic first uses a two-stage cluster analysis approach to initially group machines and assign parts, aiming to maximize grouping efficacy measures. This initial solution is then improved using a simulated annealing technique. The heuristic is tested on both binary and non-binary datasets, and results indicate it generates promising quality solutions compared to other cell formation approaches.
This document presents a new approach for forming part families and machine cells in a batch-oriented production system. The approach combines a local search heuristic with a genetic algorithm. The genetic algorithm is used to generate initial machine cell sets, while the local search heuristic considers both inter-cell movement and machine utilization to improve the groupings. The heuristic feeds back grouping efficacy results to the genetic algorithm until an optimal solution is found. The goal is to maximize grouping quality and machine utilization within cells, while minimizing inter-cell movement of parts. The approach is tested on a sample manufacturing data set, with results showing higher grouping efficacy than traditional methods.
A New Mathematical Model for Minimization of Exceptional Load in Cellular Man...IJRES Journal
This study is devoted to the cell formation problems in cellular manufacturing systems. Starting point of this study is a paper of Mahdavi et.al. which considers only a few factors of production system. In this research, processing times and the frequencies of the parts are also considered. It is assumed that the load of each machine is known and is the multiplication of the processing times and frequencies. In this case cells are formed to achieve the higher loads inside cells. Also, the proposed model is about the case when alternative technologies are available and the objective is to maximize the loads inside cells. Besides the new model, other main contribution of this study is the computational analysis. The results show that the new model is providing acceptable solution within the logical runtimes.
This document presents a stochastic extension of a cellular manufacturing system model that considers uncertain arrival rates and service times. The model is formulated as a queueing system and aims to minimize the sum of machine idleness costs, subcontracting costs, non-utilization costs, and holding costs. It introduces a chance constraint to ensure the probability that the average waiting time exceeds a critical time is below a service level. The arrival and service rates are modeled with exponential distributions. The model will be solved using GAMS software and sensitivity analysis will examine the impact of parameter changes.
Survey on Segmentation of Partially Overlapping ObjectsIRJET Journal
This document summarizes several existing methods for segmenting partially overlapping objects in digital images. It discusses challenges in segmenting overlapping objects and different approaches researchers have used, including watershed-based methods, graph cuts algorithms, active shape models, and level set methods. The goal of segmentation is to partition an image into meaningful regions to analyze objects and boundaries. Efficient segmentation of overlapping objects remains an important challenge in image processing.
ENHANCED BREAST CANCER RECOGNITION BASED ON ROTATION FOREST FEATURE SELECTIO...cscpconf
Optimization problems are dominantly being solved using Computational Intelligence. One of
the issues that can be addressed in this context is problems related to attribute subset selection
evaluation. This paper presents a computational intelligence technique for solving the
optimization problem using a proposed model called Modified Genetic Search Algorithms
(MGSA) that avoids local bad search space with merit and scaled fitness variables, detecting
and deleting bad candidate chromosomes, thereby reducing the number of individual
chromosomes from search space and subsequent iterations in next generations. This paper aims
to show that Rotation forest ensembles are useful in the feature selection method. The base
classifier is multinomial logistic regression method integrated with Haar wavelets as projection
filter and reproducing the ranks of each features with 10 fold cross validation method. It also
discusses the main findings and concludes with promising result of the proposed model. It
explores the combination of MGSA for optimization with Naïve Bayes classification. The result
obtained using proposed model MGSA is validated mathematically using Principal Component
Analysis. The goal is to improve the accuracy and quality of diagnosis of Breast cancer disease
with robust machine learning algorithms. As compared to other works in literature survey,
experimental results achieved in this paper show better results with statistical inferenc
A Hierarchical Clustering Algorithm Based Computer Aided Molecular Modeling w...IOSR Journals
This document presents a novel hierarchical clustering algorithm for color image segmentation of Haematoxylin and Eosin (H&E) stained images of colon cancer. The algorithm aims to classify differences between benign and malignant tumor cells. It involves reading an input color image, coarse representation using 25 bins, hierarchical clustering to segment the image into classes, and outputting the segmented image. Intermediate steps include filtering, normalization, and segmentation of nuclei into a separate image in MATLAB for real-time simulation. Results show the algorithm improves color segmentation accuracy over previous k-means clustering approaches and provides features for region of interest classification of benign and malignant tissues.
This document proposes a method to detect diseases in tree leaves and fruits using convolutional neural networks. The method involves preprocessing images by resizing and converting them to grayscale. Noise is removed using median filtering. Images are then segmented and features are extracted. A convolutional neural network is trained on labeled image features and used to classify new images and detect diseases. Results on test images show the preprocessing steps and segmentation being applied before classification with CNN. The method is presented as an effective way to accurately detect diseases at early stages for successful agriculture.
Ant System and Weighted Voting Method for Multiple Classifier Systems IJECEIAES
Combining multiple classifiers is considered as a general solution for classification tasks. However, there are two problems in combining multiple classifiers: constructing a diverse classifier ensemble; and, constructing an appropriate combiner. In this study, an improved multiple classifier combination scheme is propose. A diverse classifier ensemble is constructed by training them with different feature set partitions. The ant system-based algorithm is used to form the optimal feature set partitions. Weighted voting is used to combine the classifiers’ outputs by considering the strength of the classifiers prior to voting. Experiments were carried out using k-NN ensembles on benchmark datasets from the University of California, Irvine, to evaluate the credibility of the proposed method. Experimental results showed that the proposed method has successfully constructed better k-NN ensembles. Further more the proposed method can be used to develop other multiple classifier systems.
Image Mining for Flower Classification by Genetic Association Rule Mining Usi...IJAEMSJORNAL
Image mining is concerned with knowledge discovery in image databases. It is the extension of data mining algorithms to image processing domain. Image mining plays a vital role in extracting useful information from images. In computer aided plant identification and classification system the image mining will take a crucial role for the flower classification. The content image based on the low-level features such as color and textures are used to flower image classification. A flower image is segmented using a histogram threshold based method. The data set has different flower species with similar appearance (small inter class variations) across different classes and varying appearance (large intra class variations) within a class. Also the images of flowers are of different pose with cluttered background under varying lighting conditions and climatic conditions. The flower images were collected from World Wide Web in addition to the photographs taken up in a natural scene. The proposed method is based on textural features such as Gray level co-occurrence matrix (GLCM). This paper introduces multi dimensional genetic association rule mining for classification of flowers effectively. The image Data mining approach has four major steps: Preprocessing, Feature Extraction, Preparation of Transactional database and multi dimensional genetic association rule mining and classification. The purpose of our experiments is to explore the feasibility of data mining approach. Results will show that there is promise in image mining based on multi dimensional genetic association rule mining. It is well known that data mining techniques are more suitable to larger databases than the one used for these preliminary tests. Computer-aided method using association rule could assist people and improve the accuracy of flower identification. In particular, a Computer aided method based on association rules becomes more accurate with a larger dataset .Experimental results show that this new method can quickly and effectively mine potential association rules.
Analysis of texture features for wood defect classificationjournalBEEI
Selecting important features in classifying wood defects remains a challenging issue to the automated visual inspection domain. This study aims to address the extraction and analysis of features based on statistical texture on images of wood defects. A series of procedures including feature extraction using the Grey Level Dependence Matrix (GLDM) and feature analysis were executed in order to investigate the appropriate displacement and quantisation parameters that could significantly classify wood defects. Samples were taken from the KembangSemangkuk (KSK), Meranti and Merbau wood species. Findings from visual analysis and classification accuracy measures suggest that the feature set with the displacement parameter, d=2, and quantisation level, q=128, shows the highest classification accuracy. However, to achieve less computational cost, the feature set with quantisation level, q=32, shows acceptable performance in terms of classification accuracy.
Information-Theory Analysis of Cell Characteristics in Breast Cancer Patientsijbbjournal
This document summarizes a study that used information theory to analyze characteristics of breast cancer patients. The study aimed to select the most informative cytological characteristics from a set of 10 parameters. It used normalized mutual information as a measure of the information one parameter contains about another. The analysis found that "uniformity of cell size" contained the greatest amount of information about all the other parameters, suggesting it may be important for maintaining homeostasis. The results demonstrated that the proposed method can adequately select informative parameters for modeling cancer diagnosis and prognosis.
Regularized Weighted Ensemble of Deep Classifiers ijcsa
Ensemble of classifiers increases the performance of the classification since the decision of many experts
are fused together to generate the resultant decision for prediction making. Deep learning is a classification algorithm where along with the basic learning technique, fine tuning learning is done for improved precision of learning. Deep classifier ensemble learning is having a good scope of research.Feature subset selection is another for creating individual classifiers to be fused for ensemble learning. All these ensemble techniques faces ill posed problem of overfitting. Regularized weighted ensemble of deep support vector machine performs the prediction analysis on the three UCI repository problems IRIS,Ionosphere and Seed data set, thereby increasing the generalization of the boundary plot between the
classes of the data set. The singular value decomposition reduced norm 2 regularization with the two level
deep classifier ensemble gives the best result in our experiments.
IRJET- Supervised Learning Approach for Flower Images using Color, Shape and ...IRJET Journal
The document presents a supervised learning approach for classifying flower images using machine learning algorithms. It uses artificial neural networks as the classifier. The approach involves three phases: pre-processing to resize and segment images, feature extraction of color, texture, and shape features using techniques like color moments and histograms, gray-level co-occurrence matrix, and invariant moments, and classification using the neural network. The proposed system is able to classify flower images with an average accuracy of 96%.
Leave one out cross validated Hybrid Model of Genetic Algorithm and Naïve Bay...IJERA Editor
This document presents a new hybrid model for feature selection and classification that combines genetic algorithm and naive Bayes. The proposed method first uses a binary coded genetic algorithm to select a reduced subset of important features from datasets. It then applies a naive Bayes classification method to evaluate the selected features and identify the subset that achieves the highest classification accuracy. The performance of the proposed hybrid model is evaluated on eight datasets and compared to recent publications, finding it achieves satisfactory or higher classification accuracy using fewer features.
Vinayaka : A Semi-Supervised Projected Clustering Method Using Differential E...ijseajournal
- The document presents VINAYAKA, a semi-supervised projected clustering method using differential evolution.
- VINAYAKA uses a hybrid cluster validation index combining the Subspace Clustering Quality Estimate index (for internal validation) and Gini index gain (for external validation). Differential evolution optimizes this index to find optimal subspace cluster centers.
- The method is tested on the Wisconsin breast cancer dataset, and synthetic datasets are used to demonstrate that the hybrid index can identify the correct number of clusters more accurately than an internal index alone.
Determination of Material for Shaft Design Using on Grey Correlation Analysis...IJERA Editor
Machines, automobiles, aircrafts and many other applications have shaft as major mechanical component which
must have a proper design, in-order to have the efficient transmission of power from one element to another. For
the design of shaft an appropriate range of evaluation, general product form and processing methods for material
must be made. The selection of material should be done by using multiple attribute decision methods (MADM).
In this paper, Grey Correlation Analysis and TOPSIS Method is proposed in order to decide a suitable material
by considering different attributes and graphical representations are made for different attributes verse materials
and vice versa.
Texture Images Classification using Secant Lines Segments Histogramijtsrd
Texture classification is the process to classify different textures from the given images. The aim of texture classification is to classify the category of a texture image. To design an effective algorithm for texture classification, it is essential to find a set of texture features with good discriminating power. This paper presents a texture classification system using secant lines segments histogram and Euclidean Distance. Secant lines segments histogram is used to generate the features from texture images as a histogram. These features offer a better discriminating strategy for texture classification. These features are first used for training and later on for classifying the texture images. Euclidean Distance is used for distinguishing each of the known categories for classification. Ei Phyu Win | Mie Mie Tin | Pyae Phyo Thu "Texture Images Classification using Secant Lines Segments Histogram" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd27984.pdfPaper URL: https://www.ijtsrd.com/computer-science/other/27984/texture-images-classification-using-secant-lines-segments-histogram/ei-phyu-win
An Application of Genetic Algorithm for Non-restricted Space and Pre-determin...drboon
The use of a genetic algorithm is presented to solve a facility layout problem in the situation where there is non-restricted space but the ratio of plant length and width is pre-determined. A two-leveled chromosome is constructed. Six rules are established to translate the chromosome to facility design. An approach of solving a facility layout problem is proposed. A numerical example is employed to illustrate the approach.
IRJET- A Review on Application of Artificial Intelligence to Predict Strength...IRJET Journal
This document summarizes research on using artificial neural networks to predict the strength and properties of concrete. It reviews several past studies that have successfully used ANNs to model the compressive strength and durability of concrete mixtures based on input parameters like cement content, water-cement ratio, and use of admixtures or supplementary cementitious materials. The document outlines the methodology of ANN modeling and highlights key findings from previous research, including that ANNs can accurately predict concrete properties for mixtures not included in the original training data. Overall, the review shows that ANN modeling is an effective technique for predicting nonlinear relationships in concrete performance based on mixture ingredients and proportions.
Hybrid Method HVS-MRMR for Variable Selection in Multilayer Artificial Neural...IJECEIAES
The variable selection is an important technique the reducing dimensionality of data frequently used in data preprocessing for performing data mining. This paper presents a new variable selection algorithm uses the heuristic variable selection (HVS) and Minimum Redundancy Maximum Relevance (MRMR). We enhance the HVS method for variab le selection by incorporating (MRMR) filter. Our algorithm is based on wrapper approach using multi-layer perceptron. We called this algorithm a HVS-MRMR Wrapper for variables selection. The relevance of a set of variables is measured by a convex combination of the relevance given by HVS criterion and the MRMR criterion. This approach selects new relevant variables; we evaluate the performance of HVS-MRMR on eight benchmark classification problems. The experimental results show that HVS-MRMR selected a less number of variables with high classification accuracy compared to MRMR and HVS and without variables selection on most datasets. HVS-MRMR can be applied to various classification problems that require high classification accuracy.
This document discusses medium access control (MAC) protocols for cooperative diversity in wireless local area networks (WLANs). It begins with an introduction to cooperative diversity, which exploits spatial diversity by having nearby terminals cooperate in transmitting data through independent fading channels. The research community has proposed many cooperative MAC protocols that coordinate transmissions between source, relay, and destination nodes based on the IEEE 802.11 distributed coordination function. These protocols can be classified based on how the decision for cooperation is made and how helper nodes are selected. The document provides an overview of MAC protocols where the source node itself decides whether cooperation is needed and selects helper nodes, discussing their handshaking schemes, medium access schemes, and key features.
Real time energy data acquisition and alarming system for monitoring power co...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Thermal necrosis experimental investigation on thermal exposure during bone...eSAT Publishing House
This document summarizes an experimental investigation into thermal necrosis during the bone drilling process. It discusses how drill bit parameters like rotational speed, feed rate, depth of cut, and drill diameter can significantly affect bone tissue temperatures and result in thermal necrosis if not properly controlled. The document outlines previous research that found increasing the drilling speed and using smaller drill diameters can reduce temperatures. It also describes an experiment that measured temperature changes at different drilling depths and in bones of varying thickness from different animals. The conclusion is that drilling speed is important to control temperatures and speeds from 115-220mm/min were found to be most effective at reducing temperatures caused during bone drilling.
This document proposes a new method for handwritten character recognition that uses different recognition methods sequentially as filters. It begins by describing existing recognition methods like matrix matching, feature extraction, and neural networks. It then introduces three new methods: intersection count method, shape enclosed method, and centroid based method. These are combined and applied sequentially to the input as filters to recognize characters. At each step, the possible matches are reduced, improving efficiency over single methods. The method is described through an example recognizing the letter P. It shows how each step reduces the possible matches until a single character is identified. The document concludes the filter approach is more accurate and efficient than single complex methods.
Semicompatibility and fixed point theorem in fuzzy metric space using implici...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Characterization of mixed crystals of sodium chlorate and sodium bromate and ...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Ant System and Weighted Voting Method for Multiple Classifier Systems IJECEIAES
Combining multiple classifiers is considered as a general solution for classification tasks. However, there are two problems in combining multiple classifiers: constructing a diverse classifier ensemble; and, constructing an appropriate combiner. In this study, an improved multiple classifier combination scheme is propose. A diverse classifier ensemble is constructed by training them with different feature set partitions. The ant system-based algorithm is used to form the optimal feature set partitions. Weighted voting is used to combine the classifiers’ outputs by considering the strength of the classifiers prior to voting. Experiments were carried out using k-NN ensembles on benchmark datasets from the University of California, Irvine, to evaluate the credibility of the proposed method. Experimental results showed that the proposed method has successfully constructed better k-NN ensembles. Further more the proposed method can be used to develop other multiple classifier systems.
Image Mining for Flower Classification by Genetic Association Rule Mining Usi...IJAEMSJORNAL
Image mining is concerned with knowledge discovery in image databases. It is the extension of data mining algorithms to image processing domain. Image mining plays a vital role in extracting useful information from images. In computer aided plant identification and classification system the image mining will take a crucial role for the flower classification. The content image based on the low-level features such as color and textures are used to flower image classification. A flower image is segmented using a histogram threshold based method. The data set has different flower species with similar appearance (small inter class variations) across different classes and varying appearance (large intra class variations) within a class. Also the images of flowers are of different pose with cluttered background under varying lighting conditions and climatic conditions. The flower images were collected from World Wide Web in addition to the photographs taken up in a natural scene. The proposed method is based on textural features such as Gray level co-occurrence matrix (GLCM). This paper introduces multi dimensional genetic association rule mining for classification of flowers effectively. The image Data mining approach has four major steps: Preprocessing, Feature Extraction, Preparation of Transactional database and multi dimensional genetic association rule mining and classification. The purpose of our experiments is to explore the feasibility of data mining approach. Results will show that there is promise in image mining based on multi dimensional genetic association rule mining. It is well known that data mining techniques are more suitable to larger databases than the one used for these preliminary tests. Computer-aided method using association rule could assist people and improve the accuracy of flower identification. In particular, a Computer aided method based on association rules becomes more accurate with a larger dataset .Experimental results show that this new method can quickly and effectively mine potential association rules.
Analysis of texture features for wood defect classificationjournalBEEI
Selecting important features in classifying wood defects remains a challenging issue to the automated visual inspection domain. This study aims to address the extraction and analysis of features based on statistical texture on images of wood defects. A series of procedures including feature extraction using the Grey Level Dependence Matrix (GLDM) and feature analysis were executed in order to investigate the appropriate displacement and quantisation parameters that could significantly classify wood defects. Samples were taken from the KembangSemangkuk (KSK), Meranti and Merbau wood species. Findings from visual analysis and classification accuracy measures suggest that the feature set with the displacement parameter, d=2, and quantisation level, q=128, shows the highest classification accuracy. However, to achieve less computational cost, the feature set with quantisation level, q=32, shows acceptable performance in terms of classification accuracy.
Information-Theory Analysis of Cell Characteristics in Breast Cancer Patientsijbbjournal
This document summarizes a study that used information theory to analyze characteristics of breast cancer patients. The study aimed to select the most informative cytological characteristics from a set of 10 parameters. It used normalized mutual information as a measure of the information one parameter contains about another. The analysis found that "uniformity of cell size" contained the greatest amount of information about all the other parameters, suggesting it may be important for maintaining homeostasis. The results demonstrated that the proposed method can adequately select informative parameters for modeling cancer diagnosis and prognosis.
Regularized Weighted Ensemble of Deep Classifiers ijcsa
Ensemble of classifiers increases the performance of the classification since the decision of many experts
are fused together to generate the resultant decision for prediction making. Deep learning is a classification algorithm where along with the basic learning technique, fine tuning learning is done for improved precision of learning. Deep classifier ensemble learning is having a good scope of research.Feature subset selection is another for creating individual classifiers to be fused for ensemble learning. All these ensemble techniques faces ill posed problem of overfitting. Regularized weighted ensemble of deep support vector machine performs the prediction analysis on the three UCI repository problems IRIS,Ionosphere and Seed data set, thereby increasing the generalization of the boundary plot between the
classes of the data set. The singular value decomposition reduced norm 2 regularization with the two level
deep classifier ensemble gives the best result in our experiments.
IRJET- Supervised Learning Approach for Flower Images using Color, Shape and ...IRJET Journal
The document presents a supervised learning approach for classifying flower images using machine learning algorithms. It uses artificial neural networks as the classifier. The approach involves three phases: pre-processing to resize and segment images, feature extraction of color, texture, and shape features using techniques like color moments and histograms, gray-level co-occurrence matrix, and invariant moments, and classification using the neural network. The proposed system is able to classify flower images with an average accuracy of 96%.
Leave one out cross validated Hybrid Model of Genetic Algorithm and Naïve Bay...IJERA Editor
This document presents a new hybrid model for feature selection and classification that combines genetic algorithm and naive Bayes. The proposed method first uses a binary coded genetic algorithm to select a reduced subset of important features from datasets. It then applies a naive Bayes classification method to evaluate the selected features and identify the subset that achieves the highest classification accuracy. The performance of the proposed hybrid model is evaluated on eight datasets and compared to recent publications, finding it achieves satisfactory or higher classification accuracy using fewer features.
Vinayaka : A Semi-Supervised Projected Clustering Method Using Differential E...ijseajournal
- The document presents VINAYAKA, a semi-supervised projected clustering method using differential evolution.
- VINAYAKA uses a hybrid cluster validation index combining the Subspace Clustering Quality Estimate index (for internal validation) and Gini index gain (for external validation). Differential evolution optimizes this index to find optimal subspace cluster centers.
- The method is tested on the Wisconsin breast cancer dataset, and synthetic datasets are used to demonstrate that the hybrid index can identify the correct number of clusters more accurately than an internal index alone.
Determination of Material for Shaft Design Using on Grey Correlation Analysis...IJERA Editor
Machines, automobiles, aircrafts and many other applications have shaft as major mechanical component which
must have a proper design, in-order to have the efficient transmission of power from one element to another. For
the design of shaft an appropriate range of evaluation, general product form and processing methods for material
must be made. The selection of material should be done by using multiple attribute decision methods (MADM).
In this paper, Grey Correlation Analysis and TOPSIS Method is proposed in order to decide a suitable material
by considering different attributes and graphical representations are made for different attributes verse materials
and vice versa.
Texture Images Classification using Secant Lines Segments Histogramijtsrd
Texture classification is the process to classify different textures from the given images. The aim of texture classification is to classify the category of a texture image. To design an effective algorithm for texture classification, it is essential to find a set of texture features with good discriminating power. This paper presents a texture classification system using secant lines segments histogram and Euclidean Distance. Secant lines segments histogram is used to generate the features from texture images as a histogram. These features offer a better discriminating strategy for texture classification. These features are first used for training and later on for classifying the texture images. Euclidean Distance is used for distinguishing each of the known categories for classification. Ei Phyu Win | Mie Mie Tin | Pyae Phyo Thu "Texture Images Classification using Secant Lines Segments Histogram" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd27984.pdfPaper URL: https://www.ijtsrd.com/computer-science/other/27984/texture-images-classification-using-secant-lines-segments-histogram/ei-phyu-win
An Application of Genetic Algorithm for Non-restricted Space and Pre-determin...drboon
The use of a genetic algorithm is presented to solve a facility layout problem in the situation where there is non-restricted space but the ratio of plant length and width is pre-determined. A two-leveled chromosome is constructed. Six rules are established to translate the chromosome to facility design. An approach of solving a facility layout problem is proposed. A numerical example is employed to illustrate the approach.
IRJET- A Review on Application of Artificial Intelligence to Predict Strength...IRJET Journal
This document summarizes research on using artificial neural networks to predict the strength and properties of concrete. It reviews several past studies that have successfully used ANNs to model the compressive strength and durability of concrete mixtures based on input parameters like cement content, water-cement ratio, and use of admixtures or supplementary cementitious materials. The document outlines the methodology of ANN modeling and highlights key findings from previous research, including that ANNs can accurately predict concrete properties for mixtures not included in the original training data. Overall, the review shows that ANN modeling is an effective technique for predicting nonlinear relationships in concrete performance based on mixture ingredients and proportions.
Hybrid Method HVS-MRMR for Variable Selection in Multilayer Artificial Neural...IJECEIAES
The variable selection is an important technique the reducing dimensionality of data frequently used in data preprocessing for performing data mining. This paper presents a new variable selection algorithm uses the heuristic variable selection (HVS) and Minimum Redundancy Maximum Relevance (MRMR). We enhance the HVS method for variab le selection by incorporating (MRMR) filter. Our algorithm is based on wrapper approach using multi-layer perceptron. We called this algorithm a HVS-MRMR Wrapper for variables selection. The relevance of a set of variables is measured by a convex combination of the relevance given by HVS criterion and the MRMR criterion. This approach selects new relevant variables; we evaluate the performance of HVS-MRMR on eight benchmark classification problems. The experimental results show that HVS-MRMR selected a less number of variables with high classification accuracy compared to MRMR and HVS and without variables selection on most datasets. HVS-MRMR can be applied to various classification problems that require high classification accuracy.
This document discusses medium access control (MAC) protocols for cooperative diversity in wireless local area networks (WLANs). It begins with an introduction to cooperative diversity, which exploits spatial diversity by having nearby terminals cooperate in transmitting data through independent fading channels. The research community has proposed many cooperative MAC protocols that coordinate transmissions between source, relay, and destination nodes based on the IEEE 802.11 distributed coordination function. These protocols can be classified based on how the decision for cooperation is made and how helper nodes are selected. The document provides an overview of MAC protocols where the source node itself decides whether cooperation is needed and selects helper nodes, discussing their handshaking schemes, medium access schemes, and key features.
Real time energy data acquisition and alarming system for monitoring power co...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Thermal necrosis experimental investigation on thermal exposure during bone...eSAT Publishing House
This document summarizes an experimental investigation into thermal necrosis during the bone drilling process. It discusses how drill bit parameters like rotational speed, feed rate, depth of cut, and drill diameter can significantly affect bone tissue temperatures and result in thermal necrosis if not properly controlled. The document outlines previous research that found increasing the drilling speed and using smaller drill diameters can reduce temperatures. It also describes an experiment that measured temperature changes at different drilling depths and in bones of varying thickness from different animals. The conclusion is that drilling speed is important to control temperatures and speeds from 115-220mm/min were found to be most effective at reducing temperatures caused during bone drilling.
This document proposes a new method for handwritten character recognition that uses different recognition methods sequentially as filters. It begins by describing existing recognition methods like matrix matching, feature extraction, and neural networks. It then introduces three new methods: intersection count method, shape enclosed method, and centroid based method. These are combined and applied sequentially to the input as filters to recognize characters. At each step, the possible matches are reduced, improving efficiency over single methods. The method is described through an example recognizing the letter P. It shows how each step reduces the possible matches until a single character is identified. The document concludes the filter approach is more accurate and efficient than single complex methods.
Semicompatibility and fixed point theorem in fuzzy metric space using implici...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Characterization of mixed crystals of sodium chlorate and sodium bromate and ...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Overview of wireless network control protocol in smart phone deviceseSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Experimental investigation of stepped aerofoil using propeller test rigeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
An efficient monitoring system for sports person using wi fi communicationeSAT Publishing House
This document summarizes an efficient monitoring system for athletes using Wi-Fi communication. It describes using sensors to monitor athletes' vital signs like blood pressure and movements wirelessly over Wi-Fi. The monitored values are displayed on an LCD screen. It aims to give coaches and medical staff access to athletes' sensor data to analyze performance and health while ensuring athlete privacy and consent for how their data is used.
Design features of a 5 tonne day multi – stage, intermittent drainage, conti...eSAT Publishing House
This document provides details on the mechanical design of a 5 tonne per day vegetable oil solvent extraction plant. It includes calculations for the design of major components like the hopper, extractor, launder, and sumps. Dimensions and capacities are calculated based on process parameters established in a previous design. Stress analysis is performed on components like the hopper cylinder. The total volume of the designed extractor is calculated to be 2.17m3 and the estimated cost is about 3.5 million Naira.
Scheduling for interference mitigation using enhanced intercell interference ...eSAT Publishing House
This document summarizes research on scheduling algorithms for interference mitigation using enhanced inter-cell interference coordination (eICIC) in heterogeneous networks. It discusses how deploying low-power base stations (picos) within existing macro cells can improve data rates but also causes interference. eICIC and range expansion techniques are used to mitigate this interference and improve throughput. The document analyzes the performance of round robin scheduling for eICIC and finds that it maintains fairness between users while improving throughput, especially for cell-edge users under varying traffic loads.
This document summarizes a study analyzing the quality of drinking water in Bhopal, India. It examines water quality data collected over six months from the Kolar Water Treatment Plant, which supplies drinking water to 1.8 million people in Bhopal. Most water quality parameters like turbidity, pH, hardness, chlorine and sulfate levels were within permissible limits of the Bureau of Indian Standards. However, dissolved oxygen levels were slightly above limits. The document also analyzes how water quality is affected by rainfall and the plant's ability to remove turbidity through coagulation and flocculation processes. Overall, the treatment plant generally provided drinking water meeting quality standards, though some parameters required further optimization.
Signal classification of second order cyclostationarity signals using bt scld...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Thermodynamic behavior of tetrahydrofuron in p dioxane, methylcyclohexane and...eSAT Publishing House
This document summarizes a study on the thermodynamic behavior of tetrahydrofuron liquid mixtures with p-dioxane, methylcyclohexane, and cyclohexanol. The study applies an equation of state model to calculate ultrasonic velocity, density, and other thermodynamic parameters. Close agreement was found between calculated and experimental values, indicating the model provides a good representation of molecular clustering in liquid states. Parameters like minimum potential depth and hard sphere diameter were determined for the pure components and in mixtures.
Comparison of Cell formation techniques in Cellular manufacturing using three...IJERA Editor
In the present era of globalization and competitive market, cellular manufacturing has become a vital tool for
meeting the challenges of improving productivity, which is the way to sustain growth. Getting best results of
cellular manufacturing depends on the formation of the machine cells and part families. This paper examines
advantages of ART method of cell formation over array based clustering algorithms, namely ROC-2 and DCA.
The comparison and evaluation of the cell formation methods has been carried out in the study. The most
appropriate approach is selected and used to form the cellular manufacturing system. The comparison and
evaluation is done on the basis of performance measure as grouping efficiency and improvements over the
existing cellular manufacturing system is presented.
Comparison of Cell formation techniques in Cellular manufacturing using three...IJERA Editor
This document compares three cell formation techniques for cellular manufacturing: Rank Order Clustering 2 (ROC-2), Direct Clustering Analysis (DCA), and Adaptive Resonance Theory (ART). It evaluates the performance of each using grouping efficiency and the number of exceptional elements. The key findings are that ART outperforms the other two techniques, providing faster computation and the ability to handle large industrial problems. ART is an artificial neural network approach that can dynamically adapt machine-part cells. The document concludes ART is an effective method for machine-part cell formation in cellular manufacturing.
Application of Neural Network for Cell Formation in Group TechnologyIJMER
Group Technology is a method for increasing productivity of manufacturing quality products.
For improving the flexibility in manufacturing systems, cell formation is the main step in group
technology .Every manufacturing industry faces problem of productivity and their priority is to deliver
product to valuable customer in time. For fulfilling this purpose a proper engineering analysis is needed
which can reduce material handling and wait time. This can be done by cell formation. There are
various techniques which are available for cell formation and discussed by different researchers but
neural network is found the best among them due to its better and fast computation results. Here in this
paper Adaptive Resonance Theory ART1 is analyzed and proven a better way to cope up with the
manufacturing problems.
Enhancing facility layout via ant colony technique (act)Alexander Decker
This document discusses using an ant colony technique called Ant Colony System (ACS) to optimize the facility layout of a manufacturing plant. ACS was inspired by how real ants find food sources and build colonies. The research applies ACS to optimize the positions of machines and routing of parts in an electrical motor factory. Results showed ACS provided a flexible, fast solution that reduced the distance parts traveled in the plant by 500 meters, a reduction of 0.625. ACS is presented as an effective advanced intelligent technique for modifying a production process through facility layout optimization.
Single parent mating in genetic algorithm for real robotic system identificationIAESIJAI
System identification (SI) is a method of determining a mathematical model
for a system given a set of input-output data. A representation is made using
a mathematical model based on certain specified assumptions. In SI, model
structure selection is a step where a model structure perceived as an adequate
system representation is selected. A typical rule is that the final model must
have a good balance between parsimony and accuracy. As a popular search
method, genetic algorithm (GA) is used for selecting a model structure.
However, the optimality of the final model depends much on the
effectiveness of GA operators. This paper presents a mating technique
named single parent mating (SPM) in GA for use in a real robotic SI. This
technique is based on the chromosome structure of the parents such that a
single parent is sufficient in achieving mating that eases the search for the
optimal model. The results show that using three different objective
functions (Akaike information criterion, Bayesian information criterion and
parameter magnitude–based information criterion 2) respectively, GA with
the mating technique is able to find more optimal models than without the
mating technique. Validations show that the selected models using the
mating technique are acceptable.
This document introduces BioPreDyn-bench, a suite of benchmark problems for dynamic modelling in systems biology. The suite contains 6 benchmark problems ranging from medium to large-scale kinetic models of organisms such as E. coli, S. cerevisiae, D. melanogaster, and human cells. For each benchmark, the document provides a description, implementations in various formats, computational results from specific solvers, and analysis. The suite aims to serve as reference test cases to evaluate and compare parameter estimation methods for dynamic models in systems biology.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
DESIGN OF ROBUST CELLULAR MANUFACTURING SYSTEM FOR DYNAMIC.pptxssuser9e6d7e
The document describes a genetic algorithm approach for designing robust cellular manufacturing systems considering dynamic part populations and multiple processing routes. The algorithm groups machines into cells and assigns part operations to machines and cells to minimize total cost while satisfying constraints. It represents solutions as chromosomes, evaluates fitness, and uses genetic operators like crossover and mutation to evolve new solutions over generations. The approach provides flexibility in production planning and was tested on benchmark problems from literature, showing it can handle both single and multiple part routing scenarios.
The document discusses developing cell layouts in a job shop using group technology. It aims to determine the minimum machine capacity required to form inter-cellular layouts using group technology, improve machine performance measures and efficiency by eliminating unnecessary machines and implementing repetitive lots. Previous research identified formation methods but did not specify minimum capacity or performance improvement. The work to be done includes selecting machines and parts to develop a matrix, creating a new algorithm using existing notation, and designing a computational model of the new cell layout.
This paper presents a set of methods that uses a genetic algorithm for automatic test-data generation in
software testing. For several years researchers have proposed several methods for generating test data
which had different drawbacks. In this paper, we have presented various Genetic Algorithm (GA) based test
methods which will be having different parameters to automate the structural-oriented test data generation
on the basis of internal program structure. The factors discovered are used in evaluating the fitness
function of Genetic algorithm for selecting the best possible Test method. These methods take the test
populations as an input and then evaluate the test cases for that program. This integration will help in
improving the overall performance of genetic algorithm in search space exploration and exploitation fields
with better convergence rate.
An Automatic Clustering Technique for Optimal ClustersIJCSEA Journal
This document presents a new automatic clustering algorithm called Automatic Merging for Optimal Clusters (AMOC). AMOC is a two-phase iterative extension of k-means clustering that aims to automatically determine the optimal number of clusters for a given dataset. In the first phase, AMOC initializes a large number of clusters k using k-means. In the second phase, it iteratively merges the lowest probability cluster with its closest neighbor, recomputing metrics each time to evaluate if the merge improved clustering quality. The algorithm stops merging once no improvements are found. Experimental results on synthetic and real datasets show AMOC finds nearly optimal cluster structures in terms of number, compactness and separation of clusters.
Biclustering using Parallel Fuzzy Approach for Analysis of Microarray Gene Ex...CSCJournals
Biclusters are required to analyzing gene expression patterns of genes comparing rows in expression profiles and analyzing expression profiles of samples by comparing columns in gene expression matrix. In the process of biclustering we need to cluster genes and samples. The algorithm presented in this paper is based upon the two-way clustering approach in which the genes and samples are clustered using parallel fuzzy C-means clustering using message passing interface, we call it MFCM. MFCM applied for clustering on genes and samples which maximize membership function values of the data set. It is a parallelized rework of a parallel fuzzy two-way clustering algorithm for microarray gene expression data [9], to study the efficiency and parallelization improvement of the algorithm. The algorithm uses gene entropy measure to filter the clustered data to find biclusters. The method is able to get highly correlated biclusters of the gene expression dataset.
A Hybrid Genetic Algorithm-TOPSIS-Computer Simulation Approach For Optimum Op...Steven Wallach
This document describes a study that uses a hybrid genetic algorithm-TOPSIS (HGTS) approach to determine the optimal operator assignment in cellular manufacturing systems. The HGTS approach considers attributes like number of operators, lead time, waiting time, completed parts, operator utilization, and machine utilization to evaluate alternative assignment scenarios. Computer simulation is used to obtain attribute values for each scenario. HGTS aims to find the scenario with the shortest distance to an ideal scenario and farthest from a negative-ideal scenario. The proposed HGTS approach is shown to provide superior results compared to other multi-criteria decision making techniques like TOPSIS, DEA, and PCA.
Automatic Unsupervised Data Classification Using Jaya Evolutionary Algorithmaciijournal
In this paper we attempt to solve an automatic clustering problem by optimizing multiple objectives such as automatic k-determination and a set of cluster validity indices concurrently. The proposed automatic clustering technique uses the most recent optimization algorithm Jaya as an underlying optimization stratagem. This evolutionary technique always aims to attain global best solution rather than a local best solution in larger datasets. The explorations and exploitations imposed on the proposed work results to detect the number of automatic clusters, appropriate partitioning present in data sets and mere optimal values towards CVIs frontiers. Twelve datasets of different intricacy are used to endorse the performance of aimed algorithm. The experiments lay bare that the conjectural advantages of multi objective clustering optimized with evolutionary approaches decipher into realistic and scalable performance paybacks.
Load Distribution Composite Design Pattern for Genetic Algorithm-Based Autono...ijsc
The document describes a load distribution composite design pattern for genetic algorithm-based autonomic computing systems. The pattern distributes the population generated by a genetic algorithm server across multiple clients to reduce the server's load. It uses case-based reasoning, database access, and master-slave design patterns. The client evaluates portions of the population and stores results in a database. This allows the genetic algorithm to scale effectively to large problem sizes by distributing the computation workload.
LOAD DISTRIBUTION COMPOSITE DESIGN PATTERN FOR GENETIC ALGORITHM-BASED AUTONO...ijsc
Current autonomic computing systems are ad hoc solutions that are designed and implemented from the
scratch. When designing software, in most cases two or more patterns are to be composed to solve a bigger
problem. A composite design patterns shows a synergy that makes the composition more than just the sum
of its parts which leads to ready-made software architectures. As far as we know, there are no studies on
composition of design patterns for autonomic computing domain. In this paper we propose pattern-oriented
software architecture for self-optimization in autonomic computing system using design patterns
composition and multi objective evolutionary algorithms that software designers and/or programmers can
exploit to drive their work. Main objective of the system is to reduce the load in the server by distributing
the population to clients. We used Case Based Reasoning, Database Access, and Master Slave design
patterns. We evaluate the effectiveness of our architecture with and without design patterns compositions.
The use of composite design patterns in the architecture and quantitative measurements are presented. A
simple UML class diagram is used to describe the architecture.
Modified artificial immune system for single row facility layout problemIAEME Publication
One of the main optimization algorithms currently available in the research field is an Artificial Immune System where abundant applications are using this algorithm for clustering and patter recognition processes. These algorithms are providing more effective optimized results in multi-model optimization problems than Genetic Algorithm.
Modified artificial immune system for single row facility layout problemIAEME Publication
The document describes a modified artificial immune system (MAIS) algorithm for solving the single row facility layout problem (SRFLP). The SRFLP involves arranging machines in a single row to minimize material handling costs. Existing artificial immune system (AIS) algorithms have slow convergence and weak stability. The proposed MAIS uses local search around memory antibodies to improve the AIS algorithm. Simulations show MAIS achieves better results than standard AIS. The MAIS is applied to three types of SRFLP - equal distance, zero distance, and different distance between machines. The objective is to minimize the total material handling cost.
Clustered Genetic Algorithm to solve Multidimensional Knapsack Problemijtsrd
Genetic Algorithm (GA) has emerged as a powerful tool to discover optimal for multidimensional knapsack problem (MDKP). Multidimensional knapsack problem has recognized as NP-hard problem whose applications in many areas like project selection, capital budgeting, loading problems, cutting stock etc. Attempts has made to develop cluster genetic algorithm (CGA) by mean of modified selection and modified crossover operators of GA. Clustered genetic algorithm consist of (1) fuzzy roulette wheel selection for individual selection to form the mating pool (2) A different kind of crossover operator which employ hierarchical clustering method to form two clusters from individuals of mating pool. CGA performance has examined against GA with respect to 30 benchmark problems for multi-dimensional knapsack. Experimental results show that CGA has significant improvement over GA in relation to discover optimal and CPU running time. The data set for MDKP Dr. Prabha Shreeraj Nair"Clustered Genetic Algorithm to solve Multidimensional Knapsack Problem" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-4 , June 2017, URL: http://www.ijtsrd.com/papers/ijtsrd2237.pdf http://www.ijtsrd.com/computer-science/other/2237/clustered-genetic-algorithm-to-solve-multidimensional-knapsack-problem/dr-prabha-shreeraj-nair
Automatic Identification of Sub Assembly in an Assemblyishan kossambe
Assembly is a hierarchical process. It involves the
construction of subassemblies and their assembly with other
subassemblies and components. A product is split in
subassemblies at the design stage as it is not practical to
handle the design of the whole product. Splitting the
assemblies into subassemblies has the advantage of modularity
in design, manufacturing and assembly. Most complex
assemblies tend to include a number of subassemblies. There
exist methods to extract assembly mate information but
identifying subassemblies within the assembly remains a
challenge. There is a need to identify subassemblies
automatically without human interference. This paper aims at
detecting the subassemblies by making use of Application
Programming Interface (API) of the computer aided design
(CAD) software.
Similar to A multi stage heuristic for manufacturing cell (20)
Hudhud cyclone caused extensive damage in Visakhapatnam, India in October 2014, especially to tree cover. This will likely impact the local environment in several ways: increased air pollution as trees absorb less; higher temperatures without tree canopy; increased erosion and landslides. It also created large amounts of waste from destroyed trees. Proper management of solid waste is needed to prevent disease spread. Suggested measures include restoring damaged plants, building fountains to reduce heat, mandating light-colored buildings, improving waste management, and educating public on health risks. Overall, changes are needed to water, land, and waste practices to rebuild the environment after the cyclone removed green cover.
Impact of flood disaster in a drought prone area – case study of alampur vill...eSAT Publishing House
1) In September-October 2009, unprecedented heavy rainfall and dam releases caused widespread flooding in Alampur village in Mahabub Nagar district, a historically drought-prone area.
2) The flood damaged or destroyed homes, buildings, infrastructure, crops, and documents. It displaced many residents and cut off the village.
3) The socioeconomic conditions and mud-based construction of homes in the village exacerbated the flood's impacts, making damage more severe and recovery more difficult.
The document summarizes the Hudhud cyclone that struck Visakhapatnam, India in October 2014. It describes the cyclone's formation, rapid intensification to winds of 175 km/h, and landfall near Visakhapatnam. The cyclone caused extensive damage estimated at over $1 billion and at least 109 deaths in India and Nepal. Infrastructure like buildings, bridges, and power lines were destroyed. Crops and fishing boats were also damaged. The document then discusses coping strategies and improvements needed to disaster management plans to better prepare for future cyclones.
Groundwater investigation using geophysical methods a case study of pydibhim...eSAT Publishing House
This document summarizes the results of a geophysical investigation using vertical electrical sounding (VES) methods at 13 locations around an industrial area in India. The VES data was interpreted to generate geo-electric sections and pseudo-sections showing subsurface resistivity variations. Three main layers were typically identified - a high resistivity topsoil, a weathered middle layer, and a basement rock. Pseudo-sections revealed relatively more weathered areas in the northwest and southwest. Resistivity sections helped identify zones of possible high groundwater potential based on low resistivity anomalies sandwiched between more resistive layers. The study concluded the electrical resistivity method was useful for understanding subsurface geology and identifying areas prospective for groundwater exploration.
Flood related disasters concerned to urban flooding in bangalore, indiaeSAT Publishing House
1. The document discusses urban flooding in Bangalore, India. It describes how factors like heavy rainfall, population growth, and improper land use have contributed to increased flooding in the city.
2. Flooding events in 2013 are analyzed in detail. A November rainfall caused runoff six times higher than the drainage capacity, inundating low-lying residential areas.
3. Impacts of urban flooding include disrupted daily life, damaged infrastructure, and decreased economic activity in affected areas. The document calls for improved flood management strategies to better mitigate urban flooding risks in Bangalore.
Enhancing post disaster recovery by optimal infrastructure capacity buildingeSAT Publishing House
This document discusses enhancing post-disaster recovery through optimal infrastructure capacity building. It presents a model to minimize the cost of meeting demand using auxiliary capacities when disaster damages infrastructure. The model uses genetic algorithms to select optimal capacity combinations. The document reviews how infrastructure provides vital services supporting recovery activities and discusses classifying infrastructure into six types. When disaster reduces infrastructure services, a gap forms between community demands and available support, hindering recovery. The proposed research aims to identify this gap and optimize capacity selection to fill it cost-effectively.
Effect of lintel and lintel band on the global performance of reinforced conc...eSAT Publishing House
This document analyzes the effect of lintels and lintel bands on the seismic performance of reinforced concrete masonry infilled frames through non-linear static pushover analysis. Four frame models are considered: a frame with a full masonry infill wall; a frame with a central opening but no lintel/band; a frame with a lintel above the opening; and a frame with a lintel band above the opening. The results show that the full infill wall model has 27% higher stiffness and 32% higher strength than the model with just an opening. Models with lintels or lintel bands have slightly higher strength and stiffness than the model with just an opening. The document concludes lintels and lintel
Wind damage to trees in the gitam university campus at visakhapatnam by cyclo...eSAT Publishing House
1) A cyclone with wind speeds of 175-200 kph caused massive damage to the green cover of Gitam University campus in Visakhapatnam, India. Thousands of trees were uprooted or damaged.
2) A study assessed different types of damage to trees from the cyclone, including defoliation, salt spray damage, damage to stems/branches, and uprooting. Certain tree species were more vulnerable than others.
3) The results of the study can help in selecting more wind-resistant tree species for future planting and reducing damage from future storms.
Wind damage to buildings, infrastrucuture and landscape elements along the be...eSAT Publishing House
1) A visual study was conducted to assess wind damage from Cyclone Hudhud along the 27km Visakha-Bheemli Beach road in Visakhapatnam, India.
2) Residential and commercial buildings suffered extensive roof damage, while glass facades on hotels and restaurants were shattered. Infrastructure like electricity poles and bus shelters were destroyed.
3) Landscape elements faced damage, including collapsed trees that damaged pavements, and debris in parks. The cyclone wiped out over half the city's green cover and caused beach erosion around protected areas.
1) The document reviews factors that influence the shear strength of reinforced concrete deep beams, including compressive strength of concrete, percentage of tension reinforcement, vertical and horizontal web reinforcement, aggregate interlock, shear span-to-depth ratio, loading distribution, side cover, and beam depth.
2) It finds that compressive strength of concrete, tension reinforcement percentage, and web reinforcement all increase shear strength, while shear strength decreases as shear span-to-depth ratio increases.
3) The distribution and amount of vertical and horizontal web reinforcement also affects shear strength, but closely spaced stirrups do not necessarily enhance capacity or performance.
Role of voluntary teams of professional engineers in dissater management – ex...eSAT Publishing House
1) A team of 17 professional engineers from various disciplines called the "Griha Seva" team volunteered after the 2001 Gujarat earthquake to provide technical assistance.
2) The team conducted site visits, assessments, testing and recommended retrofitting strategies for damaged structures in Bhuj and Ahmedabad. They were able to fully assess and retrofit 20 buildings in Ahmedabad.
3) Factors observed that exacerbated the earthquake's impacts included unplanned construction, non-engineered buildings, improper prior retrofitting, and defective materials and workmanship. The professional engineers' technical expertise was crucial for effective post-disaster management.
This document discusses risk analysis and environmental hazard management. It begins by defining risk, hazard, and toxicity. It then outlines the steps involved in hazard identification, including HAZID, HAZOP, and HAZAN. The document presents a case study of a hypothetical gas collecting station, identifying potential accidents and hazards. It discusses quantitative and qualitative approaches to risk analysis, including calculating a fire and explosion index. The document concludes by discussing hazard management strategies like preventative measures, control measures, fire protection, relief operations, and the importance of training personnel on safety.
Review study on performance of seismically tested repaired shear wallseSAT Publishing House
This document summarizes research on the performance of reinforced concrete shear walls that have been repaired after damage. It begins with an introduction to shear walls and their failure modes. The literature review then discusses the behavior of original shear walls as well as different repair techniques tested by other researchers, including conventional repair with new concrete, jacketing with steel plates or concrete, and use of fiber reinforced polymers. The document focuses on evaluating the strength retention of shear walls after being repaired with various methods.
Monitoring and assessment of air quality with reference to dust particles (pm...eSAT Publishing House
This document summarizes a study on monitoring and assessing air quality with respect to dust particles (PM10 and PM2.5) in the urban environment of Visakhapatnam, India. Sampling was conducted in residential, commercial, and industrial areas from October 2013 to August 2014. The average PM2.5 and PM10 concentrations were within limits in residential areas but moderate to high in commercial and industrial areas. Exceedance factor levels indicated moderate pollution for residential areas and moderate to high pollution for commercial and industrial areas. There is a need for management measures like improved public transport and green spaces to combat particulate air pollution in the study areas.
Low cost wireless sensor networks and smartphone applications for disaster ma...eSAT Publishing House
This document describes a low-cost wireless sensor network and smartphone application system for disaster management. The system uses an Arduino-based wireless sensor network comprising nodes with various sensors to monitor the environment. The sensor data is transmitted to a central gateway and then to the cloud for analysis. A smartphone app connected to the cloud can detect disasters from the sensor data and send real-time alerts to users to help with early evacuation. The system aims to provide low-cost localized disaster detection and warnings to improve safety.
Coastal zones – seismic vulnerability an analysis from east coast of indiaeSAT Publishing House
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1. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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A MULTI STAGE HEURISTIC FOR MANUFACTURING CELL
FORMATION
P.Krishnananda Rao
Professor, Department of Mechanical and Manufacturing Engineering, Manipal Institute of Technology,
Karnataka, India
Abstract
Cellular manufacturing (CM) is a modern manufacturing concept based on the Group technology (GT) philosophy. CM enables a
manufacturing unit to enhance its productivity substantially through improved utilization of resources. In Cellular manufacturing
system design process the task of solving cell formation problem (machine –component grouping) is the central issue. Cell
formation problem is considered as complex one due to its combinatorial nature. Research interest is growing towards
development of novel solution methodologies for the purpose of cell formation. Even though numerous approaches have been
implemented by researchers for the task of machine-component grouping, the effectiveness of multi stage solution procedures
based on the integration of traditional and non-traditional optimization techniques needs to be investigated adequately. This
paper demonstrates the development and implementation of a multi stage heuristic based on the integration of traditional cluster
analysis technique and non- traditional simulated annealing technique for standard cell formation. The proposed heuristic is
tested using a number of binary and non-binary datasets and computational results are presented. Results indicate that proposed
heuristic is capable of generating promising quality solutions when compared with a few alternate cell forming approaches.
Key Words: Cellular manufacturing, Group technology Cell formation, Cellular manufacturing system, Cluster
analysis, Simulated annealing.
--------------------------------------------------------------------***----------------------------------------------------------------------
1. INTRODUCTION
In the present competitive business environment
manufacturing industries are striving to implement novel
strategies to enhance their profitability and productivity for
survival and growth. Cellular manufacturing (CM) is a novel
manufacturing concept which has proved to be effective in
improving the productivity of an enterprise. CM is an
application of Group technology (GT) philosophy. GT
exploits similarities between objects and groups similar
objects into homogeneous clusters. In the context of
manufacturing, GT helps in the identification of dissimilar
machine groups and part (component) families for
processing on each machine group so as to practice CM. The
task of grouping machines into cells and assigning part
families to each cell is popularly known as cell formation.
Cell formation is regarded as the first and the complex step
in Cellular manufacturing system (CMS) design process.
Due to its combinatorial nature, research interest is growing
towards implementation of novel and efficient solution
methodologies for manufacturing cell formation. Two types
of cell formation problem which have been investigated by
researchers are binary and generalized cell formations. In
binary cell formation machine groups and respective part
families are formed using the processing information of
parts present in binary (0/1) machine-component incidence
matrix (MCIM). In binary MCIM, entrry ‘1’ indicates the
requirement of a specific machine by a specific part and
‘0’ indicates the opposite. In generalized cell formation the
machine groups and the corresponding part families are
formed using the non-binary non binary MCIM containing
the processing information parts and their production data
such as processing times, production volumes, operation
sequences, alternate process routings, production costs, etc.
Binary cell formation offers rough cut solutions whereas
generalized cell formation offers realistic machine
component groupings considering the real time production
environment.
Numerous approaches have been introduced the researchers
over the years towards solving the manufacturing cell
formation problem. A review of cell forming approaches is
carried out by Grammatoula and Wilson [1],
Arora et al. [2]. Production flow analysis technique was
applied by Burbidge [3] for machine and component
grouping utilizing MCIM with binary data.
Chandrasekharan and Rajagopalan [4] introduced array
based methods for cell formation. Similarity coefficient
based cell forming approaches have been put
forth by McAuley [5] and Gupta and Seifoddini [6].
Chandrasekharan and Rajagopalan [7] and Srinivasan and
Narendran [8] introduced non- hierarchical clustering
approaches namely ZODIAC and GRAFICS for machine-
component grouping. These approaches require
fixation of total number of cells to be formed
in advance. Srinivasan et al. [9], Paydar and Sahebjamnia
[10] and Mahdavi et al.[11] demonstrated mathematical
programming based approaches for machine-component cell
formation. Even though mathematical programming based
approaches can incorporate multiple production related
factors during cell formation, they have been found to be
computationally intractable for realistically sized problems.
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Heuristic approaches have been introduced by Chen [12]
and Waghodekar and Sahu [13] binary cell formation
problem. Gupta and Devika [14] developed a novel
approach to machine-part cell formation using Mahalanobis
distance measure.
A number of non-traditional optimsation techniques such as
meta heuristics have been investigated by researchers for
solving the cell formation problem. Boctor [15],
Arkat et al. [16], Jabalameli et al.[17], Ying et al.[18]
introduced simulated annealing (SA) based approaches for
machine –component grouping. Cheng et al. [19], Paydar
and Saidi-Mehrabad [20], Arikaran and Jayabalan [21] used
genetic algorithm (GA) based approaches to cell formation
problem.. Wu et al.[22] developed tabu search (TS) based
approach for machine –part grouping. Zolfaghari and Liang
[23]carried out a comparative study of simulated annealing,
genetic algorithm and tabu search meta heuristics for
solving binary and generalized machine grouping problems
Kao and Lin [24] introduced a particle swarm optimization
(PSO) based procedure to solve the cell formation problem.
Prabhaharan et al. [25] developed an ant colony system
(ACS) based cell formation approach and found that ACS
performs better than GA. Dimopoulos and Mort [26]
solved the cell formation problem using genetic
programming (GP) approach. Majority of the above
mentioned approaches allow the presence of singleton
clusters (cells with single machine) in the solution. Presence
of singleton clusters turns the machine-component grouping
configuration unrealistic. The appraisal of numerous cell
forming approaches indicate that the effectiveness of multi
stage solution methodologies based on the integration of
traditional and non-traditional optimization techniques have
not been investigated adequately. Hence, a multistage
heuristic based on the integration of cluster analysis (CA)
and simulated annealing techniques has been demonstrated
in this paper for generating realistic cell formation solution.
The proposed heuristic is designed to offer solutions for
both binary and generalized cell formation problems
considering processing and production data of components.
Component production data considered in the present work
are machine requirement, production volume and processing
time.
2. NOTATIONS
aip Binary matrix element corresponding to
machine i and part p
ajp Binary matrix element corresponding to
machine j and part p
c Index of cells, c = 1, 2,…, C
d ij Distance between machines i and j
e Number of operations (non-zero entries) within
the matrix
ed Number of in-cell operations
eo Number of out-of-cell operations
ev Number of voids (0’s) within the diagonal
blocks
cc jid Distance between cells ic and jc ,
cim Number of machines in the cell ic,
cjm Number of machines in the cell jc ,
im Machine index in the cell ic, im = 1,2,3…
cim ,
jm Machine index in the cell jc, jm = 1,2,3…
cjm ,
ciΩ Set of machines in the cell ic,
cjΩ Set of machines in the cell jc ,
p Part index, p = 1, 2,…, N
td Total in-cell processing time
max
pt Maximum processing time of part type p
to Total out-of-cell processing time
C Total number of cells
L Number of moves at a given temperature T
M Total number of machines in the data set
Mc Number of machines in cell c
N Total number of components in the data set
S0 Current solution
S1 Neighbouring solution
T Temperature coefficient
T0 Initial temperature
Tf Final temperature or termination criterion
Vp Volume of part type p
α Cooling rate
Γ Grouping efficacy
Γg Generalised grouping efficacy
ξ(S0) Objective function value of the current solution
S0
ξ(S1) Objective function value of the neighbouring
solution S1
Ωc Set of parts assigned to cell c
∆S Difference between the objective function
values
3. DEVELOPMENT OF TWO STAGE CLUSTER
ANALYSIS BASED HEURISTIC
Cluster analysis is a traditional optimization technique
which classifies similar objects into relatively homogeneous
groups or clusters. In the present work, cluster analysis has
been implemented in two stages to obtain a solution which
is further improved by simulated annealing phase.
The cluster analysis cased heuristic includes the following
stages: problem formulation, development of first stage
clustering procedure (CA1) and development of second
stage clustering procedure (CA2). Initial machine–
component groups were obtained in the first stage and
efficient machine-component groupings were obtained in
the second stage of the CA based heuristic. Grouping
efficacy [27] and Generalised grouping efficacy [23]
measures are used to measure the goodness of the block
diagonalised form of the initial binary and non-binary
machine-component incidence matrices corresponding to
binary and generalized cell formation problems. A block-
diagonalised matrix contains non-zero entries set in blocks
along the diagonal of the matrix indicating the machine
groups and part families formed. Non-zero entries outside
the diagonal blocks are called as exceptional elements which
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Volume: 03 Issue: 02 | Feb-2014, Available @ http://www.ijret.org 93
represent the intercellular traffic by components. Higher the
exceptional elements higher is the material handling cost.
Values for abovementioned goodness measures range from
0 to 1. Higher the value means more efficient is the
machine-component grouping solution formed with lesser
intercellular moves by components.
3.1 Problem Formulation
Given the binary MCIM, AM×N = {axy}, for M machines and
N components, with regard to binary cell formation
problem, obtain the machine-component grouping solution
having maximum value for the grouping efficacy measure.
Given the non-binary MCIM, GM×N = {gxy} for M machines
and N component with regard the comprehensive cell
formation problem with each non-zero matrix entry
representing the processing time of a component on a
particular machine, and given the volume of each
component, obtain the machine-component grouping
solution having maximum value for the generalized
grouping efficacy measure.
Grouping efficacy (Γ ) is expressed as:
Γ =
φ
ψ
+
−
1
1 (1)
where
e
e0
=ψ and
e
ev
=φ
Generalized grouping efficacy (Γg) is expressed as:
Γg
∑ ∑=
Ω∈
=
+
= C
c
N
p
p
ppc
d
c
tVMt
t
1 1
max
0
(2)
This measure is based on the processing requirements of
components, production quantity, and processing or
operation times of components on machines.
3.2 Development of First stage clustering
procedure (CA1)
CA1 intended to obtain initial machine groups and part
families in the first stage of the heuristic. CA1 utilises a
machine clustering procedure, MCP to group machines
using the first distance measure and a part family formation
procedure, PFP for assignment of parts to cells.
3.2.1 Distance measure for machine grouping
A distance measure is a measure for understanding the
proximity between objects in a dataset. In the present work
,a distance measure shown in equation 3, which is a special
case of Minkowski metric [19] is used as the first distance
measure to compute the distance between any two machines
i and j for machine grouping:
−= ∑=
N
p
jpipij aad
1
(3)
Smaller value for dij indicates machines i and j are similar in
processing a set of components and have to be grouped to
form a cell to minimize intercellular moves by components.
For a non-binary data set with processing times, CP utilizes
an equivalent binary matrix formed by replacing non-binary
values with 1’s (retaining 0’s of the matrix in their original
locations) to group machines. For the machine cells formed
by CP, the corresponding part families are determined by
PFP. As per PFP, a part is assigned to a cell such that most
of its operations are performed in that cell and improved
within-cell machine utilization is achieved.
3.2.2 Development of Machine clustering procedure
(MCP)
MCP has been developed to group the given set of machines
into cells utilizing the information present in the binary. For
a non-binary dataset (MCIM) containing processing times,
clustering has been carried out utilizing an equivalent binary
matrix obtained by replacing the non-binary values in the
matrix with 1’s and retaining 0’s in their original locations.
The steps involved in MCP are as follows:
Step 1. Form machine-machine distance square matrix
by computing distance values between machine
pairs in the binary MCIM using equation 3. Use
one half of the matrix as it is symmetrical about
the diagonal.
Step 2. Select the least distance value in the matrix.
Form the first natural cell (machine group) with
associated machine pair (ij).
Step 3. Select the next least value in the distance
matrix. Any of the following states may exist
with regard to machine pair (ij).
a. One of the machines i and j has been
already assigned to a cell. In this case,
assign the other machine to buffer
(a temporary machine list) for its
assignment to a specific cell at a later
stage.
b. Neither machine i nor machine j has
been assigned to an already formed cell
and neither of the machines is assigned
to the buffer or any one of the machines
in the pair is associated with the buffer.
In this case, treat the machine pair as a
new natural cell.
c. Neither machine i nor machine j is
assigned to a previously formed cell
and both machines are present in the
buffer. In this case, do the following:
i. If the number of cells already
formed is equal to one, then treat
the machine pair as next natural
cell.
ii. If the number of cells already
formed is greater than one, then
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assign machine i and j to
respective cells previously
formed where these machines
have proximity with one of the
machines in those cells with
regard to their distance values.
d. Machines i and j have been already
assigned to the same cell or two
different cells or any one of them to an
already formed cell and the other to
the buffer. In this case, ignore the
distance value.
Repeat step 3 with regard to the remaining
distance values in the distance matrix. If the
number of machines assigned to cells equals
the total number of machines in the dataset,
terminate the clustering procedure. Otherwise
go to step 4.
Step 4. Assign the remaining unassigned machines in
the buffer to those cells where they have close
association with one of the machines in those
cells with regard to their distance values.
Step 3a prevents the inclusion of all machines into a single
cell. Since machine clusters have been formed around
natural machine pairs, singleton cluster formation is
avoided.
3.2.3 Development Part family formation
procedure (PFP)
PFP has been developed to assign part families to machine
cells formed by MCP. Steps of PFP are as follows:
Step 1. For each part in the dataset, compute the total
number of operations (‘1’entries in the binary
MCIM) performed on machines of each cell.
Step 2. Assign a part to a cell as per the following
rules:
i. If a part has maximum number of its
operations performed in a cell, then
assign the part to that cell.
ii. In case of a tie between cells due to
equal maximum number of operations,
assign that part to a cell with least
number of machines to enhance the
clustering efficiency through reduction
of voids in the block- diagonalised
MCIM.
iii. In case of a second tie between cells
due to equal least number of machines,
follow the following random part
assignment scheme to break the tie
between cells.
Random part assignment scheme :
a. Identify cells where tie occurs due
to the equal least number of
machines.
b. Assign the part to the first cell
(machine group) with least
number of machines.
3.2.4 Steps for CA1
The steps involved in CA1 are as follows:
Step 1. Obtain the initial machine groups by
implementing the clustering procedure MCP.
Step 2. Assign the part family to each cell as per PFP.
Step 3. Compute the desired cluster goodness measure
value of (Γ or Γg ).
3.3 Development Second stage clustering procedure
(CA2)
The Second stage clustering procedure, CA2 of the heuristic
has been developed to obtain improved solution in the
second stage with superior value for the chosen cluster
goodness measure. The procedure for CA2 uses the second
distance measure to compute the distance between two cells
and PFP.
3.3.1 Distance measure cell grouping
The second distance measure used in this work is shown in
equation 4. This measure has been formulated to compute
the distance between any two cells ic and jc which have
been formed by CA1.
.
(4)
A cell-cell distance square matrix containing the distance
values between cell pairs computed using equation 4 has
been utilized to obtain the final machine- component
configuration. Two cells with smaller
cc jid value indicates
the machines within them are similar in processing a group
of parts and they can be merged to form a single machine
group or cell. In this work, if the total number of cells
formed by CA1 in first stage of the heuristic is two, then no
regrouping of cells is done. If it is more than two, then the
following steps for CA2 have been adopted to regroup the
cells. However, the minimum number of cells in such case
has been limited to three to prevent the formation of very
large cells.
3.3.2 Steps for CA2
Steps involved in CA2 are as follows:
Step 1. Form cell-cell distance square matrix by
computing the distance between cell pairs based
on the binary MCIM using the equation 4. Use
one half of the matrix as it is symmetrical about
the diagonal.
Step 2. Select the least distance value from the matrix.
Represent the associated cell pair (ic jc) as a cell
group and form the single machine group (cell) by
combining the machines of cells in the cell pair.
∑ ∑ ∑
Ω∈
=
Ω∈
= =
−=
ci
cii
i
cj
cjj
j
cc
m
m
m
m
m
m
N
p
jpipji aad
1 1 1
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Step 3. Assign the part families for the revised machine
grouping solution as per PFP.
Step 4. Compute the cluster goodness measure value. If it
is superior to the value obtained from CA1, then
treat the corresponding machine-component
groupings as the best solution. Otherwise retain
the previous best solution.
Step 5. Select the next least value of the distance between
cells from the matrix. Any of the following states
may exist with regard to the cell pair (ic jc):
a. One of the two cells ic or jc of the associated
cell pair (ic jc) is already included in a cell
group. In this case, assign the other cell to
this cell group and form a single machine
group (cell) by combining the machines of
the cells in the cell group.
b. None of the cells in the associated cell pair
(ic jc) is found in the already formed cell
groups. In this case, consider the cell pair as a
new cell group and form a single machine
group (cell) by combining the machines of
the cells in the cell pair.
c. Both cells in the cell pair (ic jc) have been
already assigned to previously formed cell
groups. In this case, ignore the distance
value.
Step 6. Assign part families to the newly formed machine
groupings (cells) using PFP.
Step 7. Compute cluster goodness measure value. If it is
better than the earlier value, treat the new
machine-component groupings as the best
solution. If not, retain the previous best solution.
Step 8. Repeat the steps 5 to 7. If at any instance, the total
number of cells assigned to cell groups becomes
equal to the total number of cells formed at the
end of CA1, terminate the procedure.
4. DEVELOPMENT OF SIMULATED
ANNEALING BASED HEURISTIC
Simulated annealing [28] is regarded as a popular
randomized iterative improvement method for solving
combinatorial optimization problems. SA has simple
procedure and parameter settings compared to other random
search methods. The parameters of annealing schedule of
SA include an initial temperature (T0), final temperature or
stopping criterion (Tf), the number of moves or solutions L
attempted at each temperature and the rate of cooling α by
which temperature is reduced in each iteration of the
procedure. In the present work, instead of random
initialization, SA is initialized systematically with the best
machine grouping solution generated in the first stage by
cluster analysis. This solution has been treated as the current
solution. The number of cells considered in SA phase is as
suggested by the cluster analysis phase. Γ and Γg have
been treated as objective functions for binary and
generalized cell formation problems respectively. To
generate a neighbourhood solution from the current solution,
a perturbation scheme involving pair wise swapping of
machines between cells has been adopted in the present
work.
4.1 Selection of annealing schedule parameter
values
The values for SA parameters T0, Tf, α, and L may be
determined by trial and error proce iven problem. In the
present work, these values have been set based on the
experimentation using a randomly generated representative
data set of 16 machines and 30 components (size 16 × 30).
The performance of the proposed heuristic with regard to Γg
has been assessed for 22 random settings of T0, Tf, and α.
The value of L has been maintained constant during the
experimentation. Based on the results obtained, the values
for SA parameters have been finalized as T0 = 50.00,
Tf = 0.01, α = 0.8, and L = 10.
5. PROCEDURE FOR THE PROPOSED MULTI
STAGE HEURISTIC
The detailed procedure for cluster analysis and SA based
heuristic is as follows:
Cluster Analysis phase:
First stage:
Step 1. For binary cell formation, input the binary MCIM.
For generalized cell formation, input the
following:
(a) Non-binary MCIM with processing times as
matrix entries.
(b) Equivalent binary MCIM.
(c) Volume of each component.
Step 2. Obtain initial machine-component groups and the
chosen cluster goodness measure value by
implementing CA1.
Second stage:
Step 3. Obtain the final machine-component groups
and the improved value of the chosen cluster
goodness measure value by implementing CA2.
Step 4. Return the best value of the chosen cluster
goodness measure and the corresponding
machine-component groups.
Simulated Annealing phase:
Initialisation: Input the machine groups obtained from the
CA phase as S0 and represent its cluster goodness measure
value as ξ(S0).
Step 5. Set values for T0, Tf , α, and L.
Step 6. Neighbourhood generation: Generate a
neighbouring solution S1 by perturbing S0. Assign
part families and compute ξ(S1).
Step 7. Neighbourhood search: Compute ∆S as:
∆ S = ξ(S1 ) - ξ( S0)
6. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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Volume: 03 Issue: 02 | Feb-2014, Available @ http://www.ijret.org 96
(a) If ∆S ≥ 0, accept the candidate solution.
Set S0 = S1.
(b) If ∆S < 0, accept the candidate solution if
the probability exp(∆S / T ) is greater
than the random number generated in the
range 0 and 1. Set S0 = S1. Otherwise reject
the candidate solution. Retain S0.
Step 8. Repeat steps 5 and 6 for L number of times.
Step 9. Temperature reduction: Update (reduce) the
temperature as: T = T × α .
Step 10. Termination: If T > Tf,, go to step 5. Otherwise
terminate the search.
Step 11. Return the best objective function value, the
corresponding machine-component groupings and
the block-diagonalised MCIM.
6. COMPUTATIONAL EXPERIENCE
The proposed multistage heuristic has been coded in
C programming language and implemented on a Pentium
PC. The performance of the proposed heuristic has been
compared with an existing binary cell forming approach
known as ZODIAC [7 ] for some binary data sets taken from
the literature. Γ has been chosen as the performance
measure for the comparison. Table 1 shows the results of
comparative analysis which proves the superiority of
proposed heuristic. The performance of the proposed
heuristic has been evaluated for a non-binary data set
containing 7 machines and 8 components with components’
processing times and volumes as provided by [23]. The
solution matrix with three cells obtained by the proposed
heuristic is shown in Figure 1. The corresponding value of
Γg and that reported by [23] have been found to be 63.93%
and 62.2% respectively. This proves the ability of the
proposed heuristic to capture good quality solution.
.
Fig-1: Solution matrix for data set of size 7 × 8.
Table-1: Results of the comparative analysis
Table-2: Results from CA1, CA2 and SA phases
for non-binary data sets
Data
set
no.
Source
Size
M × N
e
Grouping efficacy,
Γ (%)
ZODIAC
Proposed
heuristic
1 [29] 5 × 7 16 56.52 62.50
2 [4] 8 × 20 91 58.33 58.72
3 [9] 10 × 20 49 100.00 100.00
4 [15] 16 × 30 121 34.90 48.52
5 [15] 16 × 30 104 58.60 59.21
6 [15] 16 × 30 92 68.60 70.00
7 [15] 16 × 30 111 26.70 45.06
8 [15] 16 × 30 107 72.70 72.73
9 [15] 16 × 30 101 76.40 76.61
10 [15] 16 × 30 114 32.00 56.82
11 [30] 18 × 24 88 41.84 47.06
12 [30] 20 × 35 135 75.14 75.14
Data
set
no.
Size
M × N
e
Generalised
grouping efficacy, Γg (%)
CA phase SA phase
CA1 CA2
1 5 × 7 14 41.44 41.44 48.10
2 7 × 11 35 45.51 45.51 49.24
3 8 × 20 61 37.32 37.32 47.20
4 8 × 20 64 43.94 43.94 48.23
5 10 × 20 85 34.23 35.73 42.81
6 10 × 20 67 35.22 38.25 41.11
7 12 × 24 96 36.55 36.55 38.12
8 12 × 24 113 34.17 34.17 38.55
9 16 × 30 187 29.68 29.68 34.66
10 20 × 35 174 30.76 31.55 34.08
|
| Parts
|
| 0 0 0 0 0 0 0 0
| 1 5 7 3 6 2 4 8
----------|----------------
Machines |
1| 4 2 3
5| 1 1 4
2| 5 2
6| 3 1
3| 2 1 4 2
7| 2 1 1 1
4| 1 2 2
|
7. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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Volume: 03 Issue: 02 | Feb-2014, Available @ http://www.ijret.org 97
CONCLSIONS
The development of a multi stage cell formation heuristic
based on the integration of cluster analysis and simulated
annealing techniques has been described in this paper. The
proposed heuristic is capable of offering realistic solutions
free of singleton clusters for binary as well as generalised
cell formation problems. The number of cells to be formed
is suggested by the heuristic and it need not be specified in
advance by the practitioner arbitrarily. Computational
results for moderately sized data sets indicate that the
proposed methodology based on the integration of
traditional and non-traditional optimization techniques
provides promising quality solutions for binary and non-
binary matrices. This framework can be further extended to
incorporate performance measures which include production
parameters other than those considered in this work.
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