This document summarizes a research paper that proposes using a genetic algorithm to solve the travelling salesman problem (TSP). It begins by defining the TSP and explaining that it is NP-hard. The document then reviews various existing approaches that have used genetic algorithms and other metaheuristics to solve TSP. It proposes a genetic algorithm with tournament selection, two-point crossover, and interchange mutation operators. The algorithm is tested on sample problems with 15 cities and is shown to find optimal or near-optimal solutions. In conclusion, the document argues that genetic algorithms can efficiently find good solutions to TSP, especially when combined with knowledge from heuristic methods.
A COMPARISON BETWEEN SWARM INTELLIGENCE ALGORITHMS FOR ROUTING PROBLEMSecij
Travelling salesman problem (TSP) is a most popular combinatorial routing problem, belongs to the class of NP-hard problems. Many approacheshave been proposed for TSP.Among them, swarm intelligence (SI) algorithms can effectively achieve optimal tours with the minimum lengths and attempt to avoid trapping in local minima points. The transcendence of each SI is depended on the nature of the problem. In our studies, there has been yet no any article, which had compared the performance of SI algorithms for TSP perfectly. In this paper,four common SI algorithms are used to solve TSP, in order to compare the performance of SI algorithms for the TSP problem. These algorithms include genetic algorithm, particle swarm optimization, ant colony optimization, and artificial bee colony. For each SI, the various parameters and operators were tested, and the best values were selected for it. Experiments oversome benchmarks fromTSPLIBshow that
artificial bee colony algorithm is the best one among the fourSI-basedmethods to solverouting problems like TSP.
GRAPH COLOURING PROBLEM BASED ON DISCRETE IMPERIALIST COMPETITIVE ALGORITHMijfcstjournal
In graph theory, Graph Colouring Problem (GCP) is an assignment of colours to vertices of any given graph such that the colours on adjacent vertices are different. The GCP is known to be an optimization and NP-hard problem.Imperialist Competitive Algorithm (ICA) is a meta-heuristic optimization and stochastic search strategy which is inspired from socio-political phenomenon of imperialistic competition. The ICA contains two main operators: the assimilation and the imperialistic competition. The ICA has excellent capabilities such as high convergence rate and better global optimum achievement. In this research, a discrete version of ICA is proposed to deal with the solution of GCP. We call this algorithm as the DICA.The performance of the proposed method is compared with Genetic Algorithm (GA) on seven well-known graph colouring benchmarks. Experimental results demonstrate the superiority of the DICA for the benchmarks. This means DICA can produce optimal and valid solutions for different GCP instances.
A study and implementation of the transit route network design problem for a ...csandit
The design of public transportation networks presup
poses solving optimization problems,
involving various parameters such as the proper mat
hematical description of networks, the
algorithmic approach to apply, and also the conside
ration of real-world, practical
characteristics such as the types of vehicles in th
e network, the frequencies of routes, demand,
possible limitations of route capacities, travel de
cisions made by passengers, the environmental
footprint of the system, the available bus technolo
gies, besides others. The current paper
presents the progress of the work that aims to stud
y the design of a municipal public
transportation system that employs middleware techn
ologies and geographic information
services in order to produce practical, realistic r
esults. The system employs novel optimization
approaches such as the particle swarm algorithms an
d also considers various environmental
parameters such as the use of electric vehicles and
the emissions of conventional ones.
A new hybrid approach for solving travelling salesman problem using ordered c...eSAT Journals
Abstract Travelling Salesman Problem is a well known NP problem. It is an optimization problem. Genetic Algorithms are the evolution techniques to solve optimization problems. In this paper a new hybrid technique using ordered cross over 1 (OX1) and greedy approach has been proposed. Experiment results shows that the proposed hybrid cross over is better than the existing cross over operator as the new operator provide a better path when executed for the same number of iterations. Keywords:- Travelling Salesman Problem, ordered cross over 1 (OX1)
Genetic Algorithm For The Travelling Salesman Problem using Enhanced Sequenti...CSCJournals
Traveling Salesman Problem (TSP) is one of the most important combinatorial optimization problems. There are many researches to improve the genetic algorithm for solving TSP. The Sequential Constructive crossover (SCX) is one of the most efficient crossover operators for solving optimization problems. In this paper, we propose a new crossover operator, named Enhanced Sequential Constructive crossover operator (ESCX), which modifies and improves the criteria of SCX operator in construction of offspring. ESCX considers, in addition to the real cost of the traversed cities, an estimation cost of the remaining tour, and it selects the next node to build the offspring based on that evaluation. The experimental results comparing the proposed crossover operator to the SCX operator on some benchmark TSPLIB instances show the effectiveness of our proposed operator.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology
A COMPARISON BETWEEN SWARM INTELLIGENCE ALGORITHMS FOR ROUTING PROBLEMSecij
Travelling salesman problem (TSP) is a most popular combinatorial routing problem, belongs to the class of NP-hard problems. Many approacheshave been proposed for TSP.Among them, swarm intelligence (SI) algorithms can effectively achieve optimal tours with the minimum lengths and attempt to avoid trapping in local minima points. The transcendence of each SI is depended on the nature of the problem. In our studies, there has been yet no any article, which had compared the performance of SI algorithms for TSP perfectly. In this paper,four common SI algorithms are used to solve TSP, in order to compare the performance of SI algorithms for the TSP problem. These algorithms include genetic algorithm, particle swarm optimization, ant colony optimization, and artificial bee colony. For each SI, the various parameters and operators were tested, and the best values were selected for it. Experiments oversome benchmarks fromTSPLIBshow that
artificial bee colony algorithm is the best one among the fourSI-basedmethods to solverouting problems like TSP.
GRAPH COLOURING PROBLEM BASED ON DISCRETE IMPERIALIST COMPETITIVE ALGORITHMijfcstjournal
In graph theory, Graph Colouring Problem (GCP) is an assignment of colours to vertices of any given graph such that the colours on adjacent vertices are different. The GCP is known to be an optimization and NP-hard problem.Imperialist Competitive Algorithm (ICA) is a meta-heuristic optimization and stochastic search strategy which is inspired from socio-political phenomenon of imperialistic competition. The ICA contains two main operators: the assimilation and the imperialistic competition. The ICA has excellent capabilities such as high convergence rate and better global optimum achievement. In this research, a discrete version of ICA is proposed to deal with the solution of GCP. We call this algorithm as the DICA.The performance of the proposed method is compared with Genetic Algorithm (GA) on seven well-known graph colouring benchmarks. Experimental results demonstrate the superiority of the DICA for the benchmarks. This means DICA can produce optimal and valid solutions for different GCP instances.
A study and implementation of the transit route network design problem for a ...csandit
The design of public transportation networks presup
poses solving optimization problems,
involving various parameters such as the proper mat
hematical description of networks, the
algorithmic approach to apply, and also the conside
ration of real-world, practical
characteristics such as the types of vehicles in th
e network, the frequencies of routes, demand,
possible limitations of route capacities, travel de
cisions made by passengers, the environmental
footprint of the system, the available bus technolo
gies, besides others. The current paper
presents the progress of the work that aims to stud
y the design of a municipal public
transportation system that employs middleware techn
ologies and geographic information
services in order to produce practical, realistic r
esults. The system employs novel optimization
approaches such as the particle swarm algorithms an
d also considers various environmental
parameters such as the use of electric vehicles and
the emissions of conventional ones.
A new hybrid approach for solving travelling salesman problem using ordered c...eSAT Journals
Abstract Travelling Salesman Problem is a well known NP problem. It is an optimization problem. Genetic Algorithms are the evolution techniques to solve optimization problems. In this paper a new hybrid technique using ordered cross over 1 (OX1) and greedy approach has been proposed. Experiment results shows that the proposed hybrid cross over is better than the existing cross over operator as the new operator provide a better path when executed for the same number of iterations. Keywords:- Travelling Salesman Problem, ordered cross over 1 (OX1)
Genetic Algorithm For The Travelling Salesman Problem using Enhanced Sequenti...CSCJournals
Traveling Salesman Problem (TSP) is one of the most important combinatorial optimization problems. There are many researches to improve the genetic algorithm for solving TSP. The Sequential Constructive crossover (SCX) is one of the most efficient crossover operators for solving optimization problems. In this paper, we propose a new crossover operator, named Enhanced Sequential Constructive crossover operator (ESCX), which modifies and improves the criteria of SCX operator in construction of offspring. ESCX considers, in addition to the real cost of the traversed cities, an estimation cost of the remaining tour, and it selects the next node to build the offspring based on that evaluation. The experimental results comparing the proposed crossover operator to the SCX operator on some benchmark TSPLIB instances show the effectiveness of our proposed operator.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology
The assignment problem is a special type of linear programming problem and it is sub class of transportation problem. Assignment problems are defined with two sets of inputs i.e. set of resources and set of demands. Hungarian algorithm is able to solve assignment problems with precisely defined demands and resources.Nowadays, many organizations and competition companies consider markets of their products. They use many salespersons to improve their organizations marketing. Salespersons travel form one city to another city for their markets. There are some problems in travelling which salespeople should go which city in minimum cost. So, travelling assignment problem is a main process for many business functions. Mie Mie Aung | Yin Yin Cho | Khin Htay | Khin Soe Myint "Minimization of Assignment Problems" 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/ijtsrd26712.pdfPaper URL: https://www.ijtsrd.com/computer-science/other/26712/minimization-of-assignment-problems/mie-mie-aung
The Solution of Maximal Flow Problems Using the Method Of Fuzzy Linear Progra...theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
In order to achieve the wide range of the robotic application it is necessary to provide iterative motions
among points of the goals. For instance, in the industry mobile robots can replace any components between
a storehouse and an assembly department. Ammunition replacement is widely used in military services.
Working place is possible in ports, airports, waste site and etc. Mobile agents can be used for monitoring if
it is necessary to observe control points in the secret place. The paper deals with path planning programme
for mobile robots. The aim of the research paper is to analyse motion-planning algorithms that contain the
design of modelling programme. The programme is needed as environment modelling to obtain the
simulation data. The simulation data give the possibility to conduct the wide analyses for selected
algorithm. Analysis means the simulation data interpretation and comparison with other data obtained
using the motion-planning. The results of the careful analysis were considered for optimal path planning
algorithms. The experimental evidence was proposed to demonstrate the effectiveness of the algorithm for
steady covered space. The results described in this work can be extended in a number of directions, and
applied to other algorithms.
New Method for Finding an Optimal Solution of Generalized Fuzzy Transportatio...BRNSS Publication Hub
In this paper, a proposed method, namely, zero average method is used for solving fuzzy transportation problems by assuming that a decision-maker is uncertain about the precise values of the transportation costs, demand, and supply of the product. In the proposed method, transportation costs, demand, and supply are represented by generalized trapezoidal fuzzy numbers. To illustrate the proposed method, a numerical example is solved. The proposed method is easy to understand and apply to real-life transportation problems for the decision-makers.
International Journal of Business and Management Invention (IJBMI)inventionjournals
International Journal of Business and Management Invention (IJBMI) is an international journal intended for professionals and researchers in all fields of Business and Management. IJBMI publishes research articles and reviews within the whole field Business and Management, 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
The Traveling salesman problem (TSP) is proved to be NP-complete in most cases. The genetic algorithm
(GA) is one of the most useful algorithms for solving this problem. In this paper a conventional GA is
compared with an improved hybrid GA in solving TSP. The improved or hybrid GA consist of
conventional GA and two local optimization strategies. The first strategy is extracting all sequential
groups including four cities of samples and changing the two central cities with each other. The second
local optimization strategy is similar to an extra mutation process. In this step with a low probability a
sample is selected. In this sample two random cities are defined and the path between these cities is
reversed. The computation results show that the proposed method also finds better paths than the
conventional GA within an acceptable computation time.
A Probabilistic Hough Transform for Opportunistic Crowd-Sensing of Moving Tra...Michiaki Tatsubori
A paper presentation at SDM 2018, San Diego, CA, USA, May 3, 2018.
Abstract:
Traffic congestion in developing cities like Nairobi, Kenya can be significantly impacted by the presence of Moving Traffic Obstacles (MTOs). These MTOs are events that temporarily exist on the road, moving with or against the direction of traffic at slower speeds. They include two-wheelers, pushcarts, animals, and pedestrians, which have quite different influence on traffic compared with static obstacles, such as potholes and speed bumps. As smart- phones and supporting 3G infrastructures are wide spread even in developing countries, recent studies enabled frugal traffic obstacle data collection from smartphones in probe cars. Assuming the opportunistic, unevenly-distributed, sparse and errorful observation of traffic obstacles, we propose an MTO detection algorithm extending an image analysis technique called Probabilistic Hough Transform for collective observations as input. Based on our experiences with a small set of real-world data collected in a smartphone-based probe car project with Nairobi City County, we conducted experiments with simulated observation data to see the effectiveness of the algorithm.
APPLICATION OF FUZZY LOGIC IN TRANSPORT PLANNINGijsc
Fuzzy logic is shown to be a very promising mathematical approach for modelling traffic and
transportation processes characterized by subjectivity, ambiguity, uncertainty and imprecision. The basic
premises of fuzzy logic systems are presented as well as a detailed analysis of fuzzy logic systems developed
to solve various traffic and transportation planning problems. Emphasis is put on the importance of fuzzy
logic systems as universal approximators in solving traffic and transportation problems. This paper
presents an analysis of the results achieved using fuzzy logic to model complex traffic and transportation
processes.
Solving Assembly Line Balancing Problem Using A Hybrid Genetic Algorithm With...inventionjournals
In this paper, we propose a hybrid genetic algorithm to solve assembly line balancing problem. We put into the optimization framework of maximizing assembly line efficiency and minimizing total idle time simultaneously. The model is able to deal with more realistic situation of assembly line balancing problem such as zoning constraints. The genetic algorithm may lack the capability of exploring the solution space effectively, so we aim to provide its exploring capability by sequentially hybridizing the well-known assignment rules heuristics with genetic algorithm.
The assignment problem is a special type of linear programming problem and it is sub class of transportation problem. Assignment problems are defined with two sets of inputs i.e. set of resources and set of demands. Hungarian algorithm is able to solve assignment problems with precisely defined demands and resources.Nowadays, many organizations and competition companies consider markets of their products. They use many salespersons to improve their organizations marketing. Salespersons travel form one city to another city for their markets. There are some problems in travelling which salespeople should go which city in minimum cost. So, travelling assignment problem is a main process for many business functions. Mie Mie Aung | Yin Yin Cho | Khin Htay | Khin Soe Myint "Minimization of Assignment Problems" 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/ijtsrd26712.pdfPaper URL: https://www.ijtsrd.com/computer-science/other/26712/minimization-of-assignment-problems/mie-mie-aung
The Solution of Maximal Flow Problems Using the Method Of Fuzzy Linear Progra...theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
In order to achieve the wide range of the robotic application it is necessary to provide iterative motions
among points of the goals. For instance, in the industry mobile robots can replace any components between
a storehouse and an assembly department. Ammunition replacement is widely used in military services.
Working place is possible in ports, airports, waste site and etc. Mobile agents can be used for monitoring if
it is necessary to observe control points in the secret place. The paper deals with path planning programme
for mobile robots. The aim of the research paper is to analyse motion-planning algorithms that contain the
design of modelling programme. The programme is needed as environment modelling to obtain the
simulation data. The simulation data give the possibility to conduct the wide analyses for selected
algorithm. Analysis means the simulation data interpretation and comparison with other data obtained
using the motion-planning. The results of the careful analysis were considered for optimal path planning
algorithms. The experimental evidence was proposed to demonstrate the effectiveness of the algorithm for
steady covered space. The results described in this work can be extended in a number of directions, and
applied to other algorithms.
New Method for Finding an Optimal Solution of Generalized Fuzzy Transportatio...BRNSS Publication Hub
In this paper, a proposed method, namely, zero average method is used for solving fuzzy transportation problems by assuming that a decision-maker is uncertain about the precise values of the transportation costs, demand, and supply of the product. In the proposed method, transportation costs, demand, and supply are represented by generalized trapezoidal fuzzy numbers. To illustrate the proposed method, a numerical example is solved. The proposed method is easy to understand and apply to real-life transportation problems for the decision-makers.
International Journal of Business and Management Invention (IJBMI)inventionjournals
International Journal of Business and Management Invention (IJBMI) is an international journal intended for professionals and researchers in all fields of Business and Management. IJBMI publishes research articles and reviews within the whole field Business and Management, 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
The Traveling salesman problem (TSP) is proved to be NP-complete in most cases. The genetic algorithm
(GA) is one of the most useful algorithms for solving this problem. In this paper a conventional GA is
compared with an improved hybrid GA in solving TSP. The improved or hybrid GA consist of
conventional GA and two local optimization strategies. The first strategy is extracting all sequential
groups including four cities of samples and changing the two central cities with each other. The second
local optimization strategy is similar to an extra mutation process. In this step with a low probability a
sample is selected. In this sample two random cities are defined and the path between these cities is
reversed. The computation results show that the proposed method also finds better paths than the
conventional GA within an acceptable computation time.
A Probabilistic Hough Transform for Opportunistic Crowd-Sensing of Moving Tra...Michiaki Tatsubori
A paper presentation at SDM 2018, San Diego, CA, USA, May 3, 2018.
Abstract:
Traffic congestion in developing cities like Nairobi, Kenya can be significantly impacted by the presence of Moving Traffic Obstacles (MTOs). These MTOs are events that temporarily exist on the road, moving with or against the direction of traffic at slower speeds. They include two-wheelers, pushcarts, animals, and pedestrians, which have quite different influence on traffic compared with static obstacles, such as potholes and speed bumps. As smart- phones and supporting 3G infrastructures are wide spread even in developing countries, recent studies enabled frugal traffic obstacle data collection from smartphones in probe cars. Assuming the opportunistic, unevenly-distributed, sparse and errorful observation of traffic obstacles, we propose an MTO detection algorithm extending an image analysis technique called Probabilistic Hough Transform for collective observations as input. Based on our experiences with a small set of real-world data collected in a smartphone-based probe car project with Nairobi City County, we conducted experiments with simulated observation data to see the effectiveness of the algorithm.
APPLICATION OF FUZZY LOGIC IN TRANSPORT PLANNINGijsc
Fuzzy logic is shown to be a very promising mathematical approach for modelling traffic and
transportation processes characterized by subjectivity, ambiguity, uncertainty and imprecision. The basic
premises of fuzzy logic systems are presented as well as a detailed analysis of fuzzy logic systems developed
to solve various traffic and transportation planning problems. Emphasis is put on the importance of fuzzy
logic systems as universal approximators in solving traffic and transportation problems. This paper
presents an analysis of the results achieved using fuzzy logic to model complex traffic and transportation
processes.
Solving Assembly Line Balancing Problem Using A Hybrid Genetic Algorithm With...inventionjournals
In this paper, we propose a hybrid genetic algorithm to solve assembly line balancing problem. We put into the optimization framework of maximizing assembly line efficiency and minimizing total idle time simultaneously. The model is able to deal with more realistic situation of assembly line balancing problem such as zoning constraints. The genetic algorithm may lack the capability of exploring the solution space effectively, so we aim to provide its exploring capability by sequentially hybridizing the well-known assignment rules heuristics with genetic algorithm.
Hybrid iterated local search algorithm for optimization route of airplane tr...IJECEIAES
The traveling salesman problem (TSP) is a very popular combinatorics problem. This problem has been widely applied to various real problems. The TSP problem has been classified as a Non-deterministic Polynomial Hard (NP-Hard), so a non-deterministic algorithm is needed to solve this problem. However, a non-deterministic algorithm can only produce a fairly good solution but does not guarantee an optimal solution. Therefore, there are still opportunities to develop new algorithms with better optimization results. This research develops a new algorithm by hybridizing three local search algorithms, namely, iterated local search (ILS) with simulated annealing (SA) and hill climbing (HC), to get a better optimization result. This algorithm aimed to solve TSP problems in the transportation sector, using a case study from the Traveling Salesman Challenge 2.0 (TSC 2.0). The test results show that the developed algorithm can optimize better by 15.7% on average and 11.4% based on the best results compared to previous studies using the TabuSA algorithm.
The Optimizing Multiple Travelling Salesman Problem Using Genetic Algorithmijsrd.com
The traveling salesman problem (TSP) supports the idea of a single salesperson traveling in a continuous trip visiting all n cities exactly once and returning to the starting point. The multiple traveling salesman problems (mTSP) is complex combinatorial optimization problem, which is a generalization of the well-known Travelling Salesman Problem (TSP), where one or more salesman can be used in the path. In this paper mTSP has also been studied and solved with GA in the form of the vehicle scheduling problem. The existing model is new models are compared to both mathematically and experimentally. This work presents a chromosome methodology setting up the MTSP to be solved using a GA.
A STUDY AND IMPLEMENTATION OF THE TRANSIT ROUTE NETWORK DESIGN PROBLEM FOR A ...cscpconf
The design of public transportation networks presupposes solving optimization problems,
involving various parameters such as the proper mathematical description of networks, the
algorithmic approach to apply, and also the consideration of real-world, practical
characteristics such as the types of vehicles in the network, the frequencies of routes, demand,
possible limitations of route capacities, travel decisions made by passengers, the environmental
footprint of the system, the available bus technologies, besides others. The current paper
presents the progress of the work that aims to study the design of a municipal public
transportation system that employs middleware technologies and geographic information
services in order to produce practical, realistic results. The system employs novel optimization
approaches such as the particle swarm algorithms and also considers various environmental
parameters such as the use of electric vehicles and the emissions of conventional ones.
Quantum inspired evolutionary algorithm for solving multiple travelling sales...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
With the widespread of smart mobile devices and the
availability of many applications that provide maps, many programs
have spread to find the closest and fastest routes between
two points on the map. While the exactness and effectiveness of
best path depend on the traffic circumstances, the system needs to
add more parameters such as real traffic density and velocity in
road. In addition, because of the restricted resources of phone devices,
it is not reasonable to be used to calculate the exact optimal
solutions by some familiar deterministic algorithms, which are
usually used to find the shortest path with a map of reasonable
node number. To resolve this issue, this paper put forward to use
the genetic algorithm to reduce the computational time. The proposed
system use the genetic algorithm to find the shortest path
time with miscellaneous situations of real traffic conditions. The
genetic algorithm is clearly demonstrate excellent result when applied
on many types of map, especially when the number of nodes
increased.
INTEGRATION OF GIS AND OPTIMIZATION ROUTINES FOR THE VEHICLE ROUTING PROBLEMijccmsjournal
This paper evokes the vehicle routing problem (VRP) which aims to determine the minimum total cost pathways for a fleet of heterogeneous vehicles to deliver a set of customers' orders. The inability of optimization algorithms alone to fully satisfy the needs of logistic managers become obvious in transportation field due to the spatial nature of such problems. In this context, we couple a geographical information system (GIS) with a metaheuristic to handle the VRP efficiently then generate a geographical solution instead of the numerical solution. A real-case instance in a Tunisian region is studied in order to
test the proposed approach.
This paper evokes the vehicle routing problem (VRP) which aims to determine the minimum total cost
pathways for a fleet of heterogeneous vehicles to deliver a set of customers' orders. The inability of
optimization algorithms alone to fully satisfy the needs of logistic managers become obvious in
transportation field due to the spatial nature of such problems. In this context, we couple a geographical
information system (GIS) with a metaheuristic to handle the VRP efficiently then generate a geographical
solution instead of the numerical solution. A real-case instance in a Tunisian region is studied in order to
test the proposed approach.
The article presents different approaches to finding the optimal solution for a problem, which extends the classical traveling salesman problem. Takes into consideration the possibility of choosing a toll highway and the standard road between two cities. Describes the experimentation system. Provides mathematical model, results of the investigation, and a conclusion.
The railway capacity optimization problem deals with the maximization of the number of trains running on
a given network per unit time. In this study, we frame this problem as a typical asymmetrical Travelling
Salesman Problem (ATSP), with the ATSP nodes representing the train arrival /departure events and the
ATSP total cost representing the total time-interval of the schedule. The application problem is then
optimized using the standard Ant Colony Optimization (ACO) algorithm. The simulation experiments
validate the formulation of the railway capacity problem as an ATSP and the ACO algorithm produces
optimal solutions superior to those produced by the domain experts.
FOLLOWING CAR ALGORITHM WITH MULTI AGENT RANDOMIZED SYSTEMijcsit
We present a new Following Car Algorithm in Microscopic Urban Traffic Models which integrates some real-life factors that need to be considered, such as the effect of random distributions in the car speed,acceleration, entry of lane… Our architecture is based on Multi-Agent Randomized Systems (MARS) developed in earlier publications
Solving real world delivery problem using improved max-min ant system with lo...ijaia
This paper presents a solution to real-world delive
ry problems (RWDPs) for home delivery services wher
e
a large number of roads exist in cities and the tra
ffic on the roads rapidly changes with time. The
methodology for finding the shortest-travel-time to
ur includes a hybrid meta-heuristic that combines a
nt
colony optimization (ACO) with Dijkstra’s algorithm
, a search technique that uses both real-time traff
ic
and predicted traffic, and a way to use a real-worl
d road map and measured traffic in Japan. We
previously proposed a hybrid ACO for RWDPs that use
d a MAX-MIN Ant System (MMAS) and proposed a
method to improve the search rate of MMAS. Since tr
affic on roads changes with time, the search rate i
s
important in RWDPs. In the current work, we combine
the hybrid ACO method with the improved MMAS.
Experimental results using a map of central Tokyo a
nd historical traffic data indicate that the propos
ed
method can find a better solution than conventional
methods.
A heuristic approach for optimizing travel planning using genetics algorithmeSAT 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
A heuristic approach for optimizing travel planning using genetics algorithmeSAT Journals
Abstract In today’s fast-paced society, everyone is caught up in the hustle and bustle of life which has resulted in ineffective Planning of their very important vacation tour. Either they spend much time on deciding what to do next, or will take many unnecessary, unfocused and inefficient steps. The main purpose of our project is to develop a Travel Planner that will allow the customer to plan the entire tour so that he visits many places in less time. The concept would be implemented using Genetics Algorithm of Artificial Intelligence which would be used as a search algorithm to find the nearest optimal travel path. Moreover, In order to reduce the running time of GA, Parallelization of Genetics Algorithm would be demonstrated using Hadoop Framework. Key Words: Genetics Algorithm, TSP, Hadoop, and MapReduce etc…
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
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