Performance evaluation of heuristic methods in solving symmetric travelling salesman problems

Background and Objective: The Travelling Salesman Problem (TSP) is a challenging problem in combinatorial optimization whose main purpose is to find the shortest path reaching all interconnected cities by straight lines.In spite of many available heuristic methods for solving TSPs, no attempts have...

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Main Authors: Lim, Yai-Fung, Hong, Pei Yee, Ramli, Razamin, Khalid, Ruzelan, Baten, Md Azizul
Format: Article
Language:English
Published: Science Alert 2016
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Online Access:http://repo.uum.edu.my/19622/1/JAI%20%209%20%201-3%20%202016%20%2012-22.pdf
http://repo.uum.edu.my/19622/
http://doi.org/10.3923/jai.2016.12.22
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Institution: Universiti Utara Malaysia
Language: English
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spelling my.uum.repo.196222016-12-07T02:11:54Z http://repo.uum.edu.my/19622/ Performance evaluation of heuristic methods in solving symmetric travelling salesman problems Lim, Yai-Fung Hong, Pei Yee Ramli, Razamin Khalid, Ruzelan Baten, Md Azizul QA Mathematics Background and Objective: The Travelling Salesman Problem (TSP) is a challenging problem in combinatorial optimization whose main purpose is to find the shortest path reaching all interconnected cities by straight lines.In spite of many available heuristic methods for solving TSPs, no attempts have been made to evaluate and compare their performances. The purpose of this study is to carry out a comparative evaluation study on Simulated Annealing (SA) and several variation of Tabu Search (TS).Materials and Method: This study considers four heuristic methods, i.e., Simulated Annealing (SA), conventional Tabu Search (TS), Improved Tabu Search (ITS) and modified Reactive Tabu Search (RTS) to solve symmetric TSPs.The algorithms were tested on five chosen benchmark problems. Their performances were compared and the appropriate algorithm for solving TSPs was then identified. The solution quality was evaluated using empirical testing, benchmark solutions and probabilistic analyses. Results: The analysis of computational results showed that the modified RTS algorithm provided a better solution quality in terms of minimizing the objective function of TSPs, while the SA algorithm was useful for obtaining instant solutions for TSPs with a large number of cities. The modified RTS algorithm also performed better compared to the existing heuristic methods. Conclusion: This study has explored the most effective heuristic method for solving TSPs based on the intended solution quality. The algorithms proposed in this study should be considered in solving symmetric travelling salesman problems. Science Alert 2016 Article PeerReviewed application/pdf en http://repo.uum.edu.my/19622/1/JAI%20%209%20%201-3%20%202016%20%2012-22.pdf Lim, Yai-Fung and Hong, Pei Yee and Ramli, Razamin and Khalid, Ruzelan and Baten, Md Azizul (2016) Performance evaluation of heuristic methods in solving symmetric travelling salesman problems. Journal of Artificial Intelligence, 9 (1). pp. 12-22. ISSN 1994-5450 http://doi.org/10.3923/jai.2016.12.22 doi:10.3923/jai.2016.12.22
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutionali Repository
url_provider http://repo.uum.edu.my/
language English
topic QA Mathematics
spellingShingle QA Mathematics
Lim, Yai-Fung
Hong, Pei Yee
Ramli, Razamin
Khalid, Ruzelan
Baten, Md Azizul
Performance evaluation of heuristic methods in solving symmetric travelling salesman problems
description Background and Objective: The Travelling Salesman Problem (TSP) is a challenging problem in combinatorial optimization whose main purpose is to find the shortest path reaching all interconnected cities by straight lines.In spite of many available heuristic methods for solving TSPs, no attempts have been made to evaluate and compare their performances. The purpose of this study is to carry out a comparative evaluation study on Simulated Annealing (SA) and several variation of Tabu Search (TS).Materials and Method: This study considers four heuristic methods, i.e., Simulated Annealing (SA), conventional Tabu Search (TS), Improved Tabu Search (ITS) and modified Reactive Tabu Search (RTS) to solve symmetric TSPs.The algorithms were tested on five chosen benchmark problems. Their performances were compared and the appropriate algorithm for solving TSPs was then identified. The solution quality was evaluated using empirical testing, benchmark solutions and probabilistic analyses. Results: The analysis of computational results showed that the modified RTS algorithm provided a better solution quality in terms of minimizing the objective function of TSPs, while the SA algorithm was useful for obtaining instant solutions for TSPs with a large number of cities. The modified RTS algorithm also performed better compared to the existing heuristic methods. Conclusion: This study has explored the most effective heuristic method for solving TSPs based on the intended solution quality. The algorithms proposed in this study should be considered in solving symmetric travelling salesman problems.
format Article
author Lim, Yai-Fung
Hong, Pei Yee
Ramli, Razamin
Khalid, Ruzelan
Baten, Md Azizul
author_facet Lim, Yai-Fung
Hong, Pei Yee
Ramli, Razamin
Khalid, Ruzelan
Baten, Md Azizul
author_sort Lim, Yai-Fung
title Performance evaluation of heuristic methods in solving symmetric travelling salesman problems
title_short Performance evaluation of heuristic methods in solving symmetric travelling salesman problems
title_full Performance evaluation of heuristic methods in solving symmetric travelling salesman problems
title_fullStr Performance evaluation of heuristic methods in solving symmetric travelling salesman problems
title_full_unstemmed Performance evaluation of heuristic methods in solving symmetric travelling salesman problems
title_sort performance evaluation of heuristic methods in solving symmetric travelling salesman problems
publisher Science Alert
publishDate 2016
url http://repo.uum.edu.my/19622/1/JAI%20%209%20%201-3%20%202016%20%2012-22.pdf
http://repo.uum.edu.my/19622/
http://doi.org/10.3923/jai.2016.12.22
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