An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP

The Traveling Salesman Problem (TSP) is a combinatorial optimization problem that is useful in a number of applications. Since there is no known polynomial-time algorithm for solving large scale TSP, metaheuristic algorithms such as Ant Colony Optimization (ACO), Bee Colony Optimization (BCO), and P...

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Main Authors: Bibi Aamirah Shafaa Emambocus, Muhammed Basheer Jasser, Muzaffar Hamzah, Aida Mustapha, Angela Amphawan
Format: Article
Language:English
English
Published: Institute of Electrical and Electronics Engineers 2021
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Online Access:https://eprints.ums.edu.my/id/eprint/33368/5/An%20enhanced%20swap%20sequence-based%20particle%20swarm%20optimization%20algorithm%20to%20solve%20tsp.ABSTRACT.pdf
https://eprints.ums.edu.my/id/eprint/33368/2/An%20enhanced%20swap%20sequence-based%20particle%20swarm%20optimization%20algorithm%20to%20solve%20tsp.pdf
https://eprints.ums.edu.my/id/eprint/33368/
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9638688
https://doi.10.1109/ACCESS.2021.3133493
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spelling my.ums.eprints.333682022-07-19T04:10:53Z https://eprints.ums.edu.my/id/eprint/33368/ An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP Bibi Aamirah Shafaa Emambocus Muhammed Basheer Jasser Muzaffar Hamzah Aida Mustapha Angela Amphawan QA75.5-76.95 Electronic computers. Computer science The Traveling Salesman Problem (TSP) is a combinatorial optimization problem that is useful in a number of applications. Since there is no known polynomial-time algorithm for solving large scale TSP, metaheuristic algorithms such as Ant Colony Optimization (ACO), Bee Colony Optimization (BCO), and Particle Swarm Optimization (PSO) have been widely used to solve TSP problems through their high quality solutions. Several variants of PSO have been proposed for solving discrete optimization problems like TSP. Among them, the basic algorithm is the Swap Sequence based PSO (SSPSO), however, it does not perform well in providing high quality solutions. To improve the performance of the swap sequence based PSO, this paper introduces an Enhanced Swap Sequence based PSO (Enhanced SSPSO) algorithm by integrating the strategies of the Expanded PSO (XPSO) in the swap sequence based PSO. This is because although XPSO is only suitable for solving continuous optimization problems, it has a high performance among the variants of PSO. In our work, the TSP problem is used to model a package delivery system in the Kuala Lumpur area. The problem set consists of 50 locations in Kuala Lumpur. Our aim is to �nd the shortest route in the delivery system by using the enhanced swap sequence based PSO. We evaluate the algorithm in terms of effectiveness and effeciency while solving TSP. To evaluate the proposed algorithm, the solutions to the TSP problem obtained from the proposed algorithm and swap sequence based PSO are compared in terms of the best solution, mean solution, and time taken to converge to the optimal solution. The proposed algorithm is found to provide better solutions with shorter paths when applied to TSP as compared to swap sequence based PSO. However, the swap sequence based PSO is found to converge faster than the proposed algorithm when applied to TSP. Institute of Electrical and Electronics Engineers 2021-12-06 Article PeerReviewed text en https://eprints.ums.edu.my/id/eprint/33368/5/An%20enhanced%20swap%20sequence-based%20particle%20swarm%20optimization%20algorithm%20to%20solve%20tsp.ABSTRACT.pdf text en https://eprints.ums.edu.my/id/eprint/33368/2/An%20enhanced%20swap%20sequence-based%20particle%20swarm%20optimization%20algorithm%20to%20solve%20tsp.pdf Bibi Aamirah Shafaa Emambocus and Muhammed Basheer Jasser and Muzaffar Hamzah and Aida Mustapha and Angela Amphawan (2021) An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP. IEEE Access, 9. pp. 164820-164836. ISSN 2169-3536 https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9638688 https://doi.10.1109/ACCESS.2021.3133493
institution Universiti Malaysia Sabah
building UMS Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sabah
content_source UMS Institutional Repository
url_provider http://eprints.ums.edu.my/
language English
English
topic QA75.5-76.95 Electronic computers. Computer science
spellingShingle QA75.5-76.95 Electronic computers. Computer science
Bibi Aamirah Shafaa Emambocus
Muhammed Basheer Jasser
Muzaffar Hamzah
Aida Mustapha
Angela Amphawan
An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
description The Traveling Salesman Problem (TSP) is a combinatorial optimization problem that is useful in a number of applications. Since there is no known polynomial-time algorithm for solving large scale TSP, metaheuristic algorithms such as Ant Colony Optimization (ACO), Bee Colony Optimization (BCO), and Particle Swarm Optimization (PSO) have been widely used to solve TSP problems through their high quality solutions. Several variants of PSO have been proposed for solving discrete optimization problems like TSP. Among them, the basic algorithm is the Swap Sequence based PSO (SSPSO), however, it does not perform well in providing high quality solutions. To improve the performance of the swap sequence based PSO, this paper introduces an Enhanced Swap Sequence based PSO (Enhanced SSPSO) algorithm by integrating the strategies of the Expanded PSO (XPSO) in the swap sequence based PSO. This is because although XPSO is only suitable for solving continuous optimization problems, it has a high performance among the variants of PSO. In our work, the TSP problem is used to model a package delivery system in the Kuala Lumpur area. The problem set consists of 50 locations in Kuala Lumpur. Our aim is to �nd the shortest route in the delivery system by using the enhanced swap sequence based PSO. We evaluate the algorithm in terms of effectiveness and effeciency while solving TSP. To evaluate the proposed algorithm, the solutions to the TSP problem obtained from the proposed algorithm and swap sequence based PSO are compared in terms of the best solution, mean solution, and time taken to converge to the optimal solution. The proposed algorithm is found to provide better solutions with shorter paths when applied to TSP as compared to swap sequence based PSO. However, the swap sequence based PSO is found to converge faster than the proposed algorithm when applied to TSP.
format Article
author Bibi Aamirah Shafaa Emambocus
Muhammed Basheer Jasser
Muzaffar Hamzah
Aida Mustapha
Angela Amphawan
author_facet Bibi Aamirah Shafaa Emambocus
Muhammed Basheer Jasser
Muzaffar Hamzah
Aida Mustapha
Angela Amphawan
author_sort Bibi Aamirah Shafaa Emambocus
title An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
title_short An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
title_full An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
title_fullStr An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
title_full_unstemmed An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
title_sort enhanced swap sequence-based particle swarm optimization algorithm to solve tsp
publisher Institute of Electrical and Electronics Engineers
publishDate 2021
url https://eprints.ums.edu.my/id/eprint/33368/5/An%20enhanced%20swap%20sequence-based%20particle%20swarm%20optimization%20algorithm%20to%20solve%20tsp.ABSTRACT.pdf
https://eprints.ums.edu.my/id/eprint/33368/2/An%20enhanced%20swap%20sequence-based%20particle%20swarm%20optimization%20algorithm%20to%20solve%20tsp.pdf
https://eprints.ums.edu.my/id/eprint/33368/
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9638688
https://doi.10.1109/ACCESS.2021.3133493
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