This paper presents an improved chaotic ant colony system algorithm (ICACS) for solving combinatorial
optimization problems. The existing algorithms still have some imperfections, we use a combination of two
different operators to improve the performance of algorithm in this work. First, 3-opt local search is used
as a framework for the implementation of the ACS to improve the solution quality; Furthermore, chaos is
proposed in the work to modify the method of pheromone update to avoid the algorithm from dropping into
local optimum, thereby finding the favorable solutions. From the experimental results, we can conclude
that ICACS has much higher quality solutions than the original ACS, and can jump over the region of the
local optimum, and escape from the trap of a local optimum successfully and achieve the best solutions.
Therefore, it’s better and more effective algorithm for TSP.
α Nearness ant colony system with adaptive strategies for the traveling sales...ijfcstjournal
On account of ant colony algorithm easy to fall into local optimum, this paper presents an improved ant
colony optimization called α-AACS and reports its performance. At first, we provide an concise description
of the original ant colony system(ACS) and introduce α-nearness based on the minimum 1-tree for ACS’s
disadvantage, which better reflects the chances of a given link being a member of an optimal tour. Then, we
improve α-nearness by computing a lower bound and propose other adaptations for ACS. Finally, we
conduct a fair competition between our algorithm and others. The results clearly show that α-AACS has a
better global searching ability in finding the best solutions, which indicates that α-AACS is an effective
approach for solving the traveling salesman problem.
Utlization Cat Swarm Optimization Algorithm for Selected Harmonic Elemination...IJPEDS-IAES
The voltage source inverter (VSI) and Current source inverter (CSI) are two
types of traditional power inverter topologies.In this paper selective
harmonic elimination (SHE) Algorithm was impelemented to CSI and results
has been investigated. Cat swarm (CSO) optimization is a new meta-heuristic
algorithm which has been used in order to tuning switching parameters in
optimized value.Objective fuction is reduction of total harmonic
distortion(THD) in inverters output currents.All of simulation has been
carried out in Matlab/Software.
α Nearness ant colony system with adaptive strategies for the traveling sales...ijfcstjournal
On account of ant colony algorithm easy to fall into local optimum, this paper presents an improved ant
colony optimization called α-AACS and reports its performance. At first, we provide an concise description
of the original ant colony system(ACS) and introduce α-nearness based on the minimum 1-tree for ACS’s
disadvantage, which better reflects the chances of a given link being a member of an optimal tour. Then, we
improve α-nearness by computing a lower bound and propose other adaptations for ACS. Finally, we
conduct a fair competition between our algorithm and others. The results clearly show that α-AACS has a
better global searching ability in finding the best solutions, which indicates that α-AACS is an effective
approach for solving the traveling salesman problem.
Utlization Cat Swarm Optimization Algorithm for Selected Harmonic Elemination...IJPEDS-IAES
The voltage source inverter (VSI) and Current source inverter (CSI) are two
types of traditional power inverter topologies.In this paper selective
harmonic elimination (SHE) Algorithm was impelemented to CSI and results
has been investigated. Cat swarm (CSO) optimization is a new meta-heuristic
algorithm which has been used in order to tuning switching parameters in
optimized value.Objective fuction is reduction of total harmonic
distortion(THD) in inverters output currents.All of simulation has been
carried out in Matlab/Software.
The first ant colony optimization (ACO) called ant system was inspired through studying of the behaviour of ants in 1991 by Macro Dorigo and co-workers. An ant colony is highly organized, in which one interacting with others through pheromone in perfect harmony. Optimization problems can be solved through simulating ant’s behaviours. Since the first ant system algorithm was proposed, there is a lot of development in ACO. In ant colony system algorithm, local pheromone is used for ants to search optimum result. However, high magnitude of computing is its deficiency and sometimes it is inefficient. Thomas Stützle etal. Introduced MAX-MIN Ant System (MMAS) in 2000. It is one of the best algorithms of ACO. It limits total pheromone in every trip or sub-union to avoid local convergence. However, the limitation of pheromone slows down convergence rate in MMAS.
IMPLEMENTATION OF DYNAMIC REMOTE OPERATED USING BAT ALGORITHMNAVIGATION EQUIP...AlameluPriyadharshini
To deliver the things without human requirement but with full safety and to detect the place path and persons using RF controller by implementing concept of drone for a smaller and to implement the same for a larger network by implementing the Bat Algorithm in Wireless Sensor Network.
A Firefly Algorithm for Optimizing Spur Gear Parameters Under Non-Lubricated ...irjes
Firefly algorithm is one of the emerging evolutionary approaches for complex and non-linear
optimization problems. It is inspired by natural firefly‟s behavior such as movement of fireflies based on
brightness and by overcoming the constraints such as light absorption, obstacles, distance, etc. In this research,
firefly‟s movement had been simulated computationally to identify the best parameters for spur gear pair by
considering the design and manufacturing constraints. The proposed algorithm was tested with the traditional
design parameters and found the results are at par in less computational time by satisfying the constraints.
Quantum Meta-Heuristic Algorithm Based on Harmony Searchinventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Cuckoo Search Algorithm: An IntroductionXin-She Yang
This presentation explains the fundamental ideas of the standard Cuckoo Search (CS) algorithm, which also contains the links to the free Matlab codes at Mathswork file exchanges and the animations of numerical simulations (video at Youtube). An example of multi-objective cuckoo search (MOCS) is also given with link to the Matlab code.
Continental division of load and balanced antIJCI JOURNAL
Increasing usability of internet is creating huge data which should be managed by the industries, but this
should not affect the processing time which may create inconvenience to end user. As cloud is emerging as
back bone of IT industry there are much enhancement needed in it Many companies are switching their
data from small storage location to Cloud, The migration is done such that the companies do not have a
burden to purchase the Infrastructure they merely have to rent out the Infrastructure but the migration
should not cost on the speed of storage or retrieval of the data from the server. Load balancing is one of the
major issue in cloud computing, but these problems are Tractable There are many algorithm for load
balancing which has advantage over the other in this paper Ant colony algorithm is studied .
Intelligent analysis of the effect of internetIJCI JOURNAL
This paper analyzes the effect of Information Technology on professionals, academicians and students in
perspective of their relations, education, job purpose, health, entertainment and electronic business that
can bring changes in society. Technology can have both positive and negative consequences for people of
different walks of life at different times. The need is to understand the true impact of internet on the society
so that people can start thinking and build a healthy society. In this paper, an empirical study is considered
60 persons; a causal loop model is formed relating the parameters on the basis of data collected. These
parameters are used to form the fuzzy dynamic model to analyze the effect of the internet on the society.
The model is analyzed and suitable solutions are proposed to counter the negative effect of internet on our
society.
INFORMATION SATURATION IN MULTISPECTRAL PIXEL LEVEL IMAGE FUSIONIJCI JOURNAL
The availability of imaging sensors operating in multiple spectral bands has led to the requirement of
image fusion algorithms that would combine the image from these sensors in an efficient way to give an
image that is more informative as well as perceptible to human eye. Multispectral image fusion is the
process of combining images from different spectral bands that are optically acquired. In this paper, we
used a pixel-level image fusion based on principal component analysis that combines satellite images of the
same scene from seven different spectral bands. The purpose of using principal component analysis
technique is that it is best method for Grayscale image fusion and gives better results. The main aim of
PCA technique is to reduce a large set of variables into a small set which still contains most of the
information that was present in the large set. The paper compares different parameters namely, entropy,
standard deviation, correlation coefficient etc. for different number of images fused from two to seven.
Finally, the paper shows that the information content in an image gets saturated after fusing four images.
The first ant colony optimization (ACO) called ant system was inspired through studying of the behaviour of ants in 1991 by Macro Dorigo and co-workers. An ant colony is highly organized, in which one interacting with others through pheromone in perfect harmony. Optimization problems can be solved through simulating ant’s behaviours. Since the first ant system algorithm was proposed, there is a lot of development in ACO. In ant colony system algorithm, local pheromone is used for ants to search optimum result. However, high magnitude of computing is its deficiency and sometimes it is inefficient. Thomas Stützle etal. Introduced MAX-MIN Ant System (MMAS) in 2000. It is one of the best algorithms of ACO. It limits total pheromone in every trip or sub-union to avoid local convergence. However, the limitation of pheromone slows down convergence rate in MMAS.
IMPLEMENTATION OF DYNAMIC REMOTE OPERATED USING BAT ALGORITHMNAVIGATION EQUIP...AlameluPriyadharshini
To deliver the things without human requirement but with full safety and to detect the place path and persons using RF controller by implementing concept of drone for a smaller and to implement the same for a larger network by implementing the Bat Algorithm in Wireless Sensor Network.
A Firefly Algorithm for Optimizing Spur Gear Parameters Under Non-Lubricated ...irjes
Firefly algorithm is one of the emerging evolutionary approaches for complex and non-linear
optimization problems. It is inspired by natural firefly‟s behavior such as movement of fireflies based on
brightness and by overcoming the constraints such as light absorption, obstacles, distance, etc. In this research,
firefly‟s movement had been simulated computationally to identify the best parameters for spur gear pair by
considering the design and manufacturing constraints. The proposed algorithm was tested with the traditional
design parameters and found the results are at par in less computational time by satisfying the constraints.
Quantum Meta-Heuristic Algorithm Based on Harmony Searchinventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Cuckoo Search Algorithm: An IntroductionXin-She Yang
This presentation explains the fundamental ideas of the standard Cuckoo Search (CS) algorithm, which also contains the links to the free Matlab codes at Mathswork file exchanges and the animations of numerical simulations (video at Youtube). An example of multi-objective cuckoo search (MOCS) is also given with link to the Matlab code.
Continental division of load and balanced antIJCI JOURNAL
Increasing usability of internet is creating huge data which should be managed by the industries, but this
should not affect the processing time which may create inconvenience to end user. As cloud is emerging as
back bone of IT industry there are much enhancement needed in it Many companies are switching their
data from small storage location to Cloud, The migration is done such that the companies do not have a
burden to purchase the Infrastructure they merely have to rent out the Infrastructure but the migration
should not cost on the speed of storage or retrieval of the data from the server. Load balancing is one of the
major issue in cloud computing, but these problems are Tractable There are many algorithm for load
balancing which has advantage over the other in this paper Ant colony algorithm is studied .
Intelligent analysis of the effect of internetIJCI JOURNAL
This paper analyzes the effect of Information Technology on professionals, academicians and students in
perspective of their relations, education, job purpose, health, entertainment and electronic business that
can bring changes in society. Technology can have both positive and negative consequences for people of
different walks of life at different times. The need is to understand the true impact of internet on the society
so that people can start thinking and build a healthy society. In this paper, an empirical study is considered
60 persons; a causal loop model is formed relating the parameters on the basis of data collected. These
parameters are used to form the fuzzy dynamic model to analyze the effect of the internet on the society.
The model is analyzed and suitable solutions are proposed to counter the negative effect of internet on our
society.
INFORMATION SATURATION IN MULTISPECTRAL PIXEL LEVEL IMAGE FUSIONIJCI JOURNAL
The availability of imaging sensors operating in multiple spectral bands has led to the requirement of
image fusion algorithms that would combine the image from these sensors in an efficient way to give an
image that is more informative as well as perceptible to human eye. Multispectral image fusion is the
process of combining images from different spectral bands that are optically acquired. In this paper, we
used a pixel-level image fusion based on principal component analysis that combines satellite images of the
same scene from seven different spectral bands. The purpose of using principal component analysis
technique is that it is best method for Grayscale image fusion and gives better results. The main aim of
PCA technique is to reduce a large set of variables into a small set which still contains most of the
information that was present in the large set. The paper compares different parameters namely, entropy,
standard deviation, correlation coefficient etc. for different number of images fused from two to seven.
Finally, the paper shows that the information content in an image gets saturated after fusing four images.
The Performance Evaluation of IEEE 802.16 Physical Layer in the Basis of Bit ...IJCI JOURNAL
Fixed Broadband Wireless Access is a promising technology which can offer high speed data rate from transmitting end to customer end which can offer high speed text, voice, and video data. IEEE 802.16 WirelessMAN is a standard that specifies medium access control layer and a set of PHY layer to fixed and mobile BWA in broad range of frequencies and it supports equipment manufacturers due to its robust performance in multipath environment. Consequently WiMAX forum has adopted this version to develop the network world wide. In this paper the performance of IEEE 802.16 OFDM PHY Layer has been investigated by using the simulation model in Matlab. The Stanford University Interim (SUI) channel models are selected for the performance evaluation of this standard. The Ideal Channel estimation is considered in this work and the performance evaluation is observed in the basis of BER.
FREQUENCY RESPONSE ANALYSIS OF 3-DOF HUMAN LOWER LIMBSIJCI JOURNAL
Frequent and prolonged expose of human body to vibrations can induce back pain and physical disorder
and degeneration of tissue. The biomechanical model of human lower limbs are modeled as a three degree
of freedom linear spring-mass-damper system to estimate forces and frequencies. Then three degree of
freedom system was analysed using state space method to find natural frequency and mode shape. A
program was develop to solve simplified equations and results were plotted and discussed in detail. The
mass, stiffness and damping coefficient of various segments are taken from references. The optimal values
of the damping ratios of the body segments are estimated, for the three degrees of freedom model. At last
resonance frequencies are found to avoid expose of lower limbs to such environment for optimum comfort.
A COMPARATIVE STUDY ON IMAGE COMPRESSION USING HALFTONING BASED BLOCK TRUNCAT...IJCI JOURNAL
In this paper scrutinizes image compression using Halftoning Based Block Truncation Coding for color
image. Many algorithms were selected likely the original Block Truncation coding, Ordered Dither Block
Truncation Coding, Error Diffusion Block Truncation Coding , and Dot Diffused Block Truncation Coding.
These above techniques are divided image into non overlapping blocks. BTC acts as the basic compression
technique but it exhibits two disadvantages such as the false contour and blocking effect. Hence halftoning
based block truncation coding (HBTC) is used to overcome the two issues. Objective measures are used to
evaluate the image degree of excellence such as Peak Signal to Noise Ratio, Mean Square Error, Structural
Similarity Index and Compression Ratio. At the end, conclusions have shown that the Dot Diffused Block
Truncation Coding algorithm outperforms the Block Truncation Coding as well as Error Diffusion Block
Truncation Coding.
Quadrant Based DIR in CWin Adaptation Mechanism for Multihop Wireless NetworkIJCI JOURNAL
In Multihop Wireless Networks, traffic forwarding capability of each node varies according to its level of contention. Each node can yield its channel access opportunity to its neighbouring nodes, so that all the nodes can evenly share the channel and have similar forwarding capability. In this manner the wireless channel is utilized effectively, which is achieved using Contention Window Adaptation Mechanism (CWAM). This mechanism achieves a higher end-to-end throughout but consumes the network power to a higher level. So, a newly proposed algorithm Quadrant- Based Directional Routing Protocol (Q-DIR) is implemented as a cross-layer with CWAM, to reduce the total network power consumption through limited flooding and also reduce the routing overheads, which eventually increases overall network throughput. This algorithm limits the broadcast region to a quadrant where the source node and the destination nodes are located. Implementation of the algorithm is done in Linux based NS-2 simulator
FUZZY-BASED ENERGY EFFICIENT METHOD FOR MULTIPLE ATTACKS IN SENSOR NETWORKS: ...IJCI JOURNAL
An adversary can easily compromise sensor nodes in wireless sensor networks, and generate multiple
attacks through compromised nodes, such as false vote injection attacks and false report injection attacks.
The false vote injection attack tries to drop legitimate reports in an intermediate node, and the false report
injection attack tries to drain the energy consumption of each node. To prevent these attacks, a
probabilistic voting-based filtering scheme (PVFS) has been proposed to select verification nodes, and to
detect fabricated votes in the reports as they occur simultaneously. In this paper, we propose a method that
improves the energy efficiency of each node and the security level of the false report injection attack, while
maintaining the detection power of the false vote injection attack. Our proposed method effectively selects
verification node with considering the conditions of each node, based on a fuzzy rule-based system. The
verification node is decided through the energy remaining level, distance level, and number of detected
false votes in the fuzzy system. We evaluated the effectiveness of the proposed method, as compared to
PVFS, when two attacks occur simultaneously in the sensor network. The experimental results show that
our method saves energy by up to 8%, by improving and maintaining the defence against these multiple
attacks
The main objective of this paper is to design and develop an automatic vehicle, fully controlled by a
computer system. The vehicle designed in the present work can move in a pre-determined path and work
automatically without the need of any human operator and it also controlled by human operator. Such a
vehicle is capable of performing wide variety of difficult tasks in space research, domestic, scientific and
industrial fields. For this purpose, an IBM compatible PC with Pentium microprocessor has been used
which performed the function of the system controller. Its parallel printer port has been used as data
communication port to interface the vehicle. A suitable software program has been developed for the
system controller to send commands to the vehicle.
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
Chaotic ANT System Optimization for Path Planning of the Mobile Robotscseij
This paper presents an improved ant system algorithm for path planning of the mobile robot under the complicated environment. To solve the drawback of the traditional ant colony system algorithm (ACS), which usually falls into the local optimum, we propose an improved ant colony system algorithm (IACS) based on chaos. Simulation experiments show that chaotic ant colony algorithm not only enhances the global search capability, but also has more effective than the traditional algorithm.
Ant Colony Optimization for Optimal Low-Pass State Variable Filter Sizing IJECEIAES
In analog filter design, discrete components values such as resistors (R) and capacitors (C) are selected from the series following constant values chosen. Exhaustive search on all possible combinations for an optimized design is not feasible. In this paper, we present an application of the Ant Colony Optimization technique (ACO) in order to selected optimal values of resistors and capacitors from different manufactured series to satisfy the filter design criteria. Three variants of the Ant Colony Optimization are applied, namely, the AS (Ant System), the MMAS (Min-Max AS) and the ACS (Ant Colony System), for the optimal sizing of the Low-Pass State Variable Filter. SPICE simulations are used to validate the obtained results/performances which are compared with already published works.
A NOVEL ANT COLONY ALGORITHM FOR MULTICAST ROUTING IN WIRELESS AD HOC NETWORKS cscpconf
The Steiner tree is the underlying model for multicast communication. This paper presents a
novel ant colony algorithm guided by problem relaxation for unconstrained Steiner tree in static
wireless ad hoc networks. The framework of the proposed algorithm is based on ant colony
system (ACS). In the first step, the ants probabilistically construct the path from the source tothe terminal nodes. These paths are then merged together to generate a Steiner tree rooted at the source. The problem is relaxed to incorporate the structural information into the heuristic value for the selection of nodes. The effectiveness of the algorithm is tested on the benchmark problems of the OR-library. Simulation results show that our algorithm can find optimal Steiner tree with high success rate.
Robot Three Dimensional Space Path-planning Applying the Improved Ant Colony ...Nooria Sukmaningtyas
To make robot avoid obstacles in 3D space, the Pheromone of Ant Colony Optimization (ACO) in
Fuzzy Control Updating is put forward, the Pheromone Updating value varies with The number of iterations
and the path-planning length by each ant . the improved Transition Probability Function is also proposed,
which makes more sense for each ant choosing next feasible point .This paper firstly, describes the Robot
Workspace Modeling and its path-planning basic method, which is followed by introducing the improved
designing of the Transition Probability Function and the method of Pheromone Fuzzy Control Updating of
ACO in detail. At the same time, the comparison of optimization between the pre-improved ACO and the
improved ACO is made. The simulation result verifies that the improved ACO is feasible and available.
In this paper, we propose an improved quantum-behaved particle swarm optimization (QPSO), introducing chaos theory into QPSO and exerting logistic map to every particle position X(t) at a certain probability. In this improved QPSO, the logistic map is used to generate a set of chaotic offsets and produce multiple positions around X(t). According to their fitness, the particle's position is updated. In order to further enhance the diversity of particles, mutation operation is introduced into and acts on one dimension of the particle's position. What's more, the chaos and mutation probabilities are carefully selected. Through several typical function experiments, its result shows that the convergence accuracy of the improved QPSO is better than those of QPSO, so it is feasible and effective to introduce chaos theory and mutation operation into QPSO.
This paper deals with the optimization of the capacity of a terminal railway station using the
Ant Colony Optimization algorithm. The capacity of the terminal station is defined as the
number of trains that depart from the station in unit interval of time. The railway capacity
optimization problem is framed as a typical symmetrical Travelling Salesman Problem (TSP),
with the TSP nodes representing the train arrival /departure events and the TSP total cost
representing the total time-interval of the schedule. The application problem is then optimized
using the ACO algorithm. The simulation experiments validate the formulation of the railway
capacity problem as a TSP and the ACO algorithm produces optimal solutions superior to those
produced by the domain experts.
This paper deals with the optimization of the capacity of a terminal railway station using the Ant Colony Optimization algorithm. The capacity of the terminal station is defined as the
number of trains that depart from the station in unit interval of time. The railway capacity
optimization problem is framed as a typical symmetrical Travelling Salesman Problem (TSP),
with the TSP nodes representing the train arrival /departure events and the TSP total cost
representing the total time-interval of the schedule. The application problem is then optimized
using the ACO algorithm. The simulation experiments validate the formulation of the railway
capacity problem as a TSP and the ACO algorithm produces optimal solutions superior to those
produced by the domain experts.
Recent research in finding the optimal path by ant colony optimizationjournalBEEI
The computation of the optimal path is one of the critical problems in graph theory. It has been utilized in various practical ranges of real world applications including image processing, file carving and classification problem. Numerous techniques have been proposed in finding optimal path solutions including using ant colony optimization (ACO). This is a nature-inspired metaheuristic algorithm, which is inspired by the foraging behavior of ants in nature. Thus, this paper study the improvement made by many researchers on ACO in finding optimal path solution. Finally, this paper also identifies the recent trends and explores potential future research directions in file carving.
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
Chaotic Secure Communication Using Iterated Filtering Method P. Karthik -Assistant Professor,
D. Gokul Prashanth -UG Scholar,
T. Gokul - UG Scholar,
Department of Electronics and Communication Engineering,
SNS College of Engineering, Coimbatore, India.
COMPUTATIONAL COMPLEXITY COMPARISON OF MULTI-SENSOR SINGLE TARGET DATA FUSION...ijccmsjournal
Target tracking using observations from multiple sensors can achieve better estimation performance than a single sensor. The most famous estimation tool in target tracking is Kalman filter. There are several mathematical approaches to combine the observations of multiple sensors by use of Kalman filter. An
important issue in applying a proper approach is computational complexity. In this paper, four data fusion algorithms based on Kalman filter are considered including three centralized and one decentralized methods. Using MATLAB, computational loads of these methods are compared while number of sensors
increases. The results show that inverse covariance method has the best computational performance if the number of sensors is above 20. For a smaller number of sensors, other methods, especially group sensors, are more appropriate..
Similar to An improved ant colony algorithm based on (20)
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
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Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
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Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
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An improved ant colony algorithm based on
1. International Journal on Cybernetics & Informatics (IJCI) Vol. 3, No. 5, October 2014
AN IMPROVED ANT COLONY ALGORITHM BASED ON
3-OPT AND CHAOS FOR TRAVELLING SALESMAN
PROBLEM
Qingping Yu1 ,Xiaoming You1 and Sheng Liu2
1
College of Electronic and Electrical Engineering, Shanghai University of Engineering
Science, Shanghai 201620, China
2 School of Management, Shanghai University of Engineering Science
Shanghai, 201620, China
ABSTRACT
This paper presents an improved chaotic ant colony system algorithm (ICACS) for solving combinatorial
optimization problems. The existing algorithms still have some imperfections, we use a combination of two
different operators to improve the performance of algorithm in this work. First, 3-opt local search is used
as a framework for the implementation of the ACS to improve the solution quality; Furthermore, chaos is
proposed in the work to modify the method of pheromone update to avoid the algorithm from dropping into
local optimum, thereby finding the favorable solutions. From the experimental results, we can conclude
that ICACS has much higher quality solutions than the original ACS, and can jump over the region of the
local optimum, and escape from the trap of a local optimum successfully and achieve the best solutions.
Therefore, it’s better and more effective algorithm for TSP.
KEYWORDS
Ant colony system algorithm, 3-opt, Chaos, Travelling Salesman Problem
1. INTRODUCTION
Swarm intelligence is an emerging evolutionary computation method that takes inspiration from
the social behaviors of insects and of other animals, getting more and more attention from
researchers. In particular, [1] ants have inspired a number of methods and techniques among
which the most studied and the most successful one is the general purpose optimization technique
known as ant colony optimization (ACO). ACO algorithm is a heuristic in which a colony of
artificial ants cooperates in finding good solutions [2]. Ants release the pheromone on the path to
mark some favorable paths and communicate through pheromones with other ants of colony. As
time goes on, the higher the concentration of the pheromone is on the shorter path from their nest
to the food source. Thus, most ants tend to the path with highest pheromone intensity i.e., the
shortest path.
The ant colony optimization (ACO) algorithm was proposed by Dorigo and his colleagues as a
method for solving optimization problems [3], and developed by Dorigo, referred to as ant
system(AS). Ant colony system (ACS) is one of the most successful ACO algorithms which
achieve a much better performance than ant system (AS) which was introduced by Colorni,
DOI: 10.5121/ijci.2014.3501 1
2. International Journal on Cybernetics & Informatics (IJCI) Vol. 3, No. 5, October 2014
Dorgio and Maniezzo. In this work, ACS has been chosen as an original algorithm for solving
travelling salesman problem (TSP), and will be improved by two strategies.
The traveling salesman problem (TSP) is a classical combinatorial optimization problem which is
to find a cost-minimal Hamiltonian cycle, i.e. a cycle in a graph that contains each node exactly
once [4].Moreover, TSP is the famous NP-hard problem even though to descript the problem is
very simple, it is very difficult to solve, and to obtain the optimal solution of such problems
requires extremely long running time and a great storage space, so existing computers could not
be completed. ACS algorithm as an approximation algorithm to solve TSP reflects the
combination of global and local search, showing good optimization results.
Now, TSP has become a standard test for heuristic algorithms whether to find the optimal
solutions. So the ACS can be applied to the TSP . In this work, we proposed an ICACS algorithm
for TSP, based on 3-opt and chaos, and applied successfully to eil51
KroA200
pr264 and Lin318 in TSP problems. This paper is organized as follows: In Section 2, we further
2
KroA100
to study the original ACS, and give a brief description of TSP. Section 3 presents our approach
and describe in detail its main components. In the next Section, we perform simulation on TSP
which contains a different number of nodes and relate this analysis to the performance of original
ACS. Moreover, we explore the importance of the operators proposed in this work to the overall
algorithm performance. Conclusions are provided in the last Section.
2. ANT COLONY SYSTEM ALGORITHM (ACS) FOR TSP.
It is well known that ants find a path from nest to the food source very quickly by using indirect
communication via pheromones. As ants pass the path it release pheromone trail that can be
discovered by other ants. The path more ants pass, more pheromones are deposited. Because ants
move according to the intensity of pheromones, the richer the pheromone trail on a path is, the
more likely it would be followed by other ants. Hence, ants can construct the shortest way from
their nest to the food sources and back [5]. This ants’ behavior inspired researchers to build an
algorithmic framework that uses artificial ants to solve combinational optimization problems [6].
In the following, we will provide a formal definition of the basic ACS.
2.1. Ant Colony System Algorithm
In this work, ant colony system has been chosen as an original algorithm for solving TSP
problem. Here we give a brief description of ACS algorithm:
In ACS, the most interesting thing is the transition rules to ants’ searching solutions. When an ant
chooses the next nodes, it no longer completely obeys the previous experience, but it has a certain
probability to choose the shorter routers with higher pheromone intensity. It is called
pseudorandom proportional rule, defined by Dorigo and Stülzle [3] as:
{[ ] }
( )
b
t h
£ =
max q q
0
0
arg ,
il jl
,
k
ij
j
J p q q
(2.1-1)
Where q is a random variable uniformly distributed in[0,1] (qÎ[0,1]) , 0 q is a parameter
according to the previous empirical values used in this case for the best possible
move 0 (q Î[0,1]) , k is an ant, i, j are the initial and the next node, l is a candidate solution that
3. International Journal on Cybernetics Informatics (IJCI) Vol. 3, No. 5, October 2014
ant k have not travel the node in a loop, J is a random function gained from the probability
distribution k
h = is a
D = D (2.1-4)
d x (2.2-2)
3
ij p (see 2.1-2), and it will be chose by the ant k if q q0 .
t h
k ij ij
ij
=
[ ] k
i
l N ij ij
p
a b
a b
t h
Î
(2.1-2)
Parameter b determines the relative influence of the heuristic information, ij h (
1
) ij
ij d
heuristics function that is defined to the inverse of the distance between node i and j . k
i N is the
set of candidate nodes connected to node i , with respect to ant k . ij t represents the pheromone
from node i to node j , After constructing its tour, only the ant to find the shortest path to the
current loop was allowed to update the pheromone by applying the pheromone updating rule (2.1-
3), which accelerates the convergence of the algorithm to some extent.
(t) (1 ) (t) (t) ij ij ij t = −j t +jDt (2.1-3)
t t
1
n
ij
k
ij
k
=
With j in (0, 1), and (t) ij Dt is the quantity of pheromone deposited by the ant k between time
t and t+1 on the edge (i, j) . In addition to the global update rule, ACS uses the ant-cycle
updating rule. An ant-cycle system information update model is
, (i, j) belong to best lo
Q
0, otherwis
p
e
o
k
ij k
arc
=
Dt L
(2.1-5)
represents the intensity of the pheromone, it affects the convergence speed of algorithm to some
extent, k L denotes the total length that the ant k passed in this cycle .
2.2. Description of the Traveling Salesman Problem
Given a digraphG = (V,E) , where V = {1,2,L,n} presents city set and E presents edge set.
Variables are defined as follows [7]:
1 (if the edge (i, j) in the loop)
x
ij 0 otherwise
=
(2.2-1)
So, TSP problem can be descripted by linear programming:
min ij ij
i j
4. International Journal on Cybernetics Informatics (IJCI) Vol. 3, No. 5, October 2014
4
= =
ij
{ }
,
1 (i 1,...,n), ( )
1 (j 1,...,n), (b)
s. t .
0,1 (i, j 1,...n; i j), (c)
1 (S V;2 n 2), (d)
i
ij
j
ij
ij
i j s
x a
x
x
x S S
Î
= =
Î = ¹
£ − Ì £ £ −
(2.2-3)
Where n presents the number of cities, ij d is the Euclidean distance between city i and city j ,
and it was calculated by using 2 2 ( ) ( ) ij i j i j d = x − x + y − y . If the edge (i, j) in the loop,
1 ij x = , else, 0 ij x = . V presents the city set and the set S is a subset of V , S is the number of
elements of set S . In the formula expressions (2.2-3), the constraint items (a) , (b) , (c) ensure
there is only one path to the city as a starting point and one path to the city as a ending point,
Similarly, constraint items (d) indicate that sub-loop set of constraints can limit the feasible
solutions constitute a loop.
3. THE IMPROVED CHAOTIC ANT COLONY SYSTEM (ICACS) FOR TSP
In this section we will introduce the two strategies used in ACS in this work. One is the
introduction of the chaotic disturbance to change the update way of the pheromone, to
avoid the algorithm from dropping into local optimal. The other is the 3-opt that is used
to improve the solution quality.
3.1. Improved Ant Colony System Algorithm based on 3-OPT
A 3-OPT move changes a tour by replacing 3 edges from the tour by 3 edges in such a way that a
shorter tour is achieved. Given a feasible TSP tour, the algorithm repeatedly performs exchanges
that reduce the length of the current tour, until a tour is reached for which no exchanges yields an
improvement [8]. This process may be repeated many times from initial tours generated in some
randomized way to an optimal rout.
Let T is the current tour without a 3-OPT operation. Set { } 1 2 X , , , i = x x L x and
{ } 1 2 Y , , , i = y y L y , if the edges of X are deleted from T and replaced by the edges of Y ,
thereby gaining a better tour. The two sets X and Y are empty initially, with the number of
iterations increase, they are established element by element. i x and i y must share an endpoint,
and so must i y and i 1 x + . If 1 q denotes one of the two points of 1 x , we have in general:
( ) 2 1 2 , i i i x q q − = , ( ) 2 2 1 , i i i y q q − = and ( ) 1 2 1 2 2 , i i i x q q + + + = for i ³1 [8]. Note that the exchange of
edges X with edges Y which results in a tour is that the chain is closed (see figure 3.1.1), and
the result of an close tour by 3-opt move shows follow(see figure 3.1.2).
5. International Journal on Cybernetics Informatics (IJCI) Vol. 3, No. 5, October 2014
5
2i+1 t
i+1 X
2i+2 t
i y
i+1 y
i t2
2i−1 t
i X
Fig. 3.1.1 Restricting the choice of 1 , , i i i x y x + and i 1 y +
2 X
1 Y
3 X
2 Y
1 X
3 Y
2 X
1 Y
3 X
2 Y
1 X
3 Y
Fig.3.1.2 A 3-opt move. 1 2 3 x , x , x are replaced by 1 2 3 y , y , y
The improved ant colony system algorithm based on 3-opt has greatly improved the accuracy of
the solutions, but did not find the optimal solution, still need to be further improved. The
simulation data refer to the table(4.2).
3.2. Improvement based on chaos
Chaos is different from random, which does not mean it is completely disordered, but includes in
the orderly disorder, i.e., it is implicated that local random and global stability in the chaos. The
main characteristics of chaos are that pseudo-randomness, ergodicity and sensitivity to initial
conditions.
When ant colony algorithm is initialized, pheromone on every path are equally so that ants choose
the path with same probability, and it is difficult to make ants to find a better path quickly from a
large number of the chaotic path, leading a slow convergence. So to use chaos operator is
necessary that it can increase the searching efficiency by the random and ergodic of chaos [9]. At
present, there is no strict definition to chaos. Generally, the state of random motion will be called
chaos obtained from deterministic equations. Logistics mapping as a typical chaotic system is
6. International Journal on Cybernetics Informatics (IJCI) Vol. 3, No. 5, October 2014
used in the work which has already been the foundation of the chaos optimization algorithm,
iterative formula is as follows:
[ ] ( ] 1 0 (1 ),k 0,1,2,...; xk μ xk x 0,1 μ 3, 4 + = − = Î Î (3.2-1)
For each identified, we can obtain corresponding series 1 2 3 , , ,... k x x x x . By discussing the value of
μ , we can easily see that: when 0 μ £1, system dynamics shape is very simple, only one
periodic point 0 x = 0 ; When1 μ 3, the system dynamics shape is also simple, two-cycle point
− ; when 3 £ μ £ 4 , forming a very complex system dynamics, the system by the period-doubling
6
1
0,1
m
to chaos. Here is the Logistic map with Matlab simulation. Let the initial system m is
0.5, the number of iteration is 200, and the μ = 0.5, 2,3,3.6,3.8,4 , draw the k x corresponding
to different μ .
7. International Journal on Cybernetics Informatics (IJCI) Vol. 3, No. 5, October 2014
Where μ is the control parameter, when μ = 4 , 0 0 £ x £1 , logistic completely drops into
chaotic state.
Ant colony is based on the positive feedback principle, to a certain extent, speeding up the
evolutionary process, but there are some shortcomings, such as phenomenon of stagnation or fall
into local optimal solution. Improved measures of chaotic disturbance added to adjust the amount
of information, by adding the amount of the chaotic scramble to make the solution out of the local
extreme range. Equation (2.1-3) is amended as Equation (3.2-2):
( 1) (1 ) ( ) ( ) ij ij ij ij t t + = −j t t +jDt t + qx (3.2-2)
7
where ij x is a chaotic variable obtained from the formula (3.2-1) iteration; q is a coefficient.
3.3 The Procedure of Improved Chaotic Ant Colony System (ICACS)
We design new algorithms ICACS based on the two improving strategies presented in this paper.
In this section, we describe the specific steps of the ICACS algorithm. The steps of the algorithm
described in detail as follows:
Step 1.Chaotic initialization, initialize the pheromone of all path section, set the iteration
number i = 0 .
Step 2. Put the starting city into k tabu , choose one subsequent node j to move according to (2.1-
1), finally put node j into k tabu .
Step 3.Loop (2) until each ant find a closed tour, calculate the tour length k L of ant k , and record
the current optimal solution, adjust the current optimal solution by 3-opt operate.
Step 5.Update the pheromone intensity of paths which is shorter than i L (it has already set in this
work) by formula (3.2-2).
Step 6.The number of iterations plus 1.
Step 7.If the number of iteration reach the maximum number of iterations and find the same
solutions, output the best solution.
Step 8.To clear the k tabu of each and move to (2)
4. EXPERIMENTS AND SIMULATION
In this section, the simulation is implemented in Matlab, we describe the performance of the
improved algorithm in the work and analyze the experiment results as a function of various
parameters.
To examine the effectiveness of the two sorts of strategies, a series of standard TSP problems are
employed. The settings of the parameters of the improved chaotic ant colony system (ICACS)
algorithms refer to the follow table (Table4.1)
8. International Journal on Cybernetics Informatics (IJCI) Vol. 3, No. 5, October 2014
8
Table 4.1 ICACS parameters (present work)
Parameter a b j 0 q μ
Value 1 2 0.1 0.9 4
Table 4.2 report the experimental results for the two operators used in this work on TSP
problems. As can be seen, tour quality is acceptable. The convergence comparison is as Figure
4.1.
Table 4.2 Comparison of the results in TSP instances
Data set
Algorithm
Obtained
solution
Optimual
solution IR
eil51 ICACS
ACS+3-opt
ACS
426.21
428.87
430.67
426 0
0.67%
1.10%
kroA100 ICACS
ACS+3-opt
ACS
21282.39
21294.78
21571.56
21282 0
0.06%
1.36%
KroA200 ICACS
ACS+3-opt
ACS
29369.57
29385.93
29775.43
29368 0
0.06%
1.39%
pr264 ICACS
ACS+3-opt
ACS
49139.72
49165.60
49978.72
49135 0.01%
0.06%
1.72%
Lin318 ICACS
ACS+3-opt
ACS
42185.91
43238.95
44067.76
42029 0.37%
2.88%
4.85%
−
onatained solution optimual solution
= )
(Note: IR
%
optimual solution
9. International Journal on Cybernetics Informatics (IJCI) Vol. 3, No. 5, October 2014
9
Figure 4.1 The convergence comparison of ICACS with other algorithm using KroA 150.
5. CONCLUSIONS
This work focused on how to improve the performance of ACS algorithm. And we adopt two
improving strategies employed by the original ACS algorithm: improvement based on 3-opt to
improve the local search capability and improvement based on chaos to modify the update of
pheromone trails. Through a number of experiments, the effectiveness and advantages of the
strategies are verified. Specifically, firstly, improvement based on 3-opt can improve the quality
of solutions. Secondly, improvement based on chaos can avoid the algorithm from dropping into
local optimal and improve the probability of algorithms to find optimal solution. These two
strategies possess their own features and offer a clear guideline for designing the new ACO
algorithm. In the future, more experiments and further research about the improved strategies are
required.
Further study should be suggested to explore the better management for the optimal setting of the
parameters of ACO algorithms, which will be very helpful in the application.
ACKNOWLEDGEMENTS
The authors gratefully acknowledge the support of Innovation Program of Shanghai Municipal
Education Commission (Grant No.12ZZ185), Natural Science Foundation of China (Grant
No.61075115), Foundation of No. XKCZ1212. Xiao-Ming You is corresponding author.
REFERENCES
[1] Nan Zhao , Zhilu Wu, Yaqin Zhao, Taifan Quan: Ant colony optimization algorithm with mutation
mechanism and its applications. Expert Systems with Applications 37
[2] Rubem Matimoto Koide,Gustavo von Zeska de França andMarco Antônio Luersen: An ant colony
algorithm applied to lay-up optimization of laminated composite plates. Latin American journal of
solids and structures, 2013: 491-504
[3] Dorigo, M., Maniezzo, V., Colorni, A.: Ant system: optimization by a colony of cooperating agents.
IEEE Transactions on Systems, Man, and Cybernetics-Part B 26(1), 29–41 (1996)
10. International Journal on Cybernetics Informatics (IJCI) Vol. 3, No. 5, October 2014
[4] TORE GRU¨ NERT, Stefan Irnich, A Note on Single Alternating Cycle Neighborhoods for the TSP.
10
Journal of Heuristics, 11: 135–146, 2005
[5] Rongwei Gan, Qingshun Guo, Huiyou Chang, and Yang Yi: Improved ant colony optimization
algorithm for the traveling salesman problems. Journal of Systems Engineering and Electronics Vol.
21, No. 2, April 2010, pp.329–333
[6] Timo Kötzing • Frank Neumann • Heiko Röglin •Carsten Witt, Theoretical analysis of two ACO
approaches for the traveling salesman problem. Swarm Intelligence (2012) 6:1–21.
[7] Lixiang Li, Haipeng Peng, Yixian Yang: Chaos Ant Colony Algorithm and Applications [M].Beijing:
China Science and Technology Press, 2013:186-208
[8] Keld Helsgaun, General k-opt submoves for the Lin–Kernighan TSP heuristic. Math. Prog. Comp.
(2009) 1:119–163
[9] Yunwu, W. (2009). Application of chaos ant colony algorithm in web service composition based on
QoS. International Forum on Information Technology and Applications, 172(2), 225–227.
Authors
Qing-ping Yu is currently studying in Mechanical and Electronic Engineering from
Shanghai University of Engineering Science, China, where she is working toward the
Master degree. Her current research interests include ant colony algorithm, their design
and develop in Embedded system.
Xiao-Ming You received her M.S. degree in computer science from Wuhan University in
1993, and her Ph.D. degree in computer science from East China University of Science
and Technology in 2007. Her research interests include swarm intelligent systems,
distributed parallel processing and evolutionary computing. She now works in Shanghai
University of Engineering Science as a professor.