A modified two-part wolf pack search algorithm for the multiple traveling salesmen problem

Chen, Y; Jia, Z; Ai, X; Yang, D; Yu, J

A modified two-part wolf pack search algorithm for the multiple traveling salesmen problem

Chen, Y

Jia, Z Ai, X Yang, D Yu, J

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Publisher:: ELSEVIER SCIENCE BV
Publication Type:: Journal Article
Citation:: Applied Soft Computing Journal, 2017, 61, pp. 714-725
Issue Date:: 2017-12-01

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Field	Value	Language
dc.contributor.author	Chen, Y https://orcid.org/0000-0003-2756-7050
dc.contributor.author	Jia, Z
dc.contributor.author	Ai, X
dc.contributor.author	Yang, D
dc.contributor.author	Yu, J
dc.date.accessioned	2022-10-25T00:25:00Z
dc.date.available	2022-10-25T00:25:00Z
dc.date.issued	2017-12-01
dc.identifier.citation	Applied Soft Computing Journal, 2017, 61, pp. 714-725
dc.identifier.issn	1568-4946
dc.identifier.issn	1872-9681
dc.identifier.uri	http://hdl.handle.net/10453/162651
dc.description.abstract	This paper proposes a modified two-part wolf pack search (MTWPS) algorithm updated by the two-part individual encoding approach as well as the transposition and extension (TE) operation for the multiple travelling salesmen problem (MTSP). Firstly, the two-part individual encoding approach is introduced into the original WPS algorithm for MTSP, which is named the two-part wolf pack search (TWPS) algorithm, to minimize the size of the problem search space. Secondly, the analysis of the convergence rate performance is presented to illustrate the reasonability of the maximum terminal generation of the novel TWPS algorithm deeply. Then, based on the definition of the global reachability, the TWPS algorithm is modified by the TE operation further, which can greatly enhance the search ability of the TWPS algorithm. Finally, focusing on the objective of minimizing the total travel distance and the longest tour, comparisons of the robustness and the optimality between different algorithms are presented, and experimental results show that the MTWPS algorithm can obtain higher solution quality than the other the ones of the other two methods
dc.language	English
dc.publisher	ELSEVIER SCIENCE BV
dc.relation.ispartof	Applied Soft Computing Journal
dc.relation.isbasedon	10.1016/j.asoc.2017.08.041
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0102 Applied Mathematics, 0801 Artificial Intelligence and Image Processing, 0806 Information Systems
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	A modified two-part wolf pack search algorithm for the multiple traveling salesmen problem
dc.type	Journal Article
utslib.citation.volume	61
utslib.for	0102 Applied Mathematics
utslib.for	0801 Artificial Intelligence and Image Processing
utslib.for	0806 Information Systems
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access	*
dc.date.updated	2022-10-25T00:24:59Z
pubs.publication-status	Published
pubs.volume	61

Abstract:

This paper proposes a modified two-part wolf pack search (MTWPS) algorithm updated by the two-part individual encoding approach as well as the transposition and extension (TE) operation for the multiple travelling salesmen problem (MTSP). Firstly, the two-part individual encoding approach is introduced into the original WPS algorithm for MTSP, which is named the two-part wolf pack search (TWPS) algorithm, to minimize the size of the problem search space. Secondly, the analysis of the convergence rate performance is presented to illustrate the reasonability of the maximum terminal generation of the novel TWPS algorithm deeply. Then, based on the definition of the global reachability, the TWPS algorithm is modified by the TE operation further, which can greatly enhance the search ability of the TWPS algorithm. Finally, focusing on the objective of minimizing the total travel distance and the longest tour, comparisons of the robustness and the optimality between different algorithms are presented, and experimental results show that the MTWPS algorithm can obtain higher solution quality than the other the ones of the other two methods

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http://hdl.handle.net/10453/162651