Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/29359
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMcMenemy, Paulen_UK
dc.contributor.authorVeerapen, Nadarajenen_UK
dc.contributor.authorAdair, Jasonen_UK
dc.contributor.authorOchoa, Gabrielaen_UK
dc.contributor.editorLiefooghe, Aen_UK
dc.contributor.editorPaquete, Len_UK
dc.date.accessioned2019-04-19T00:04:44Z-
dc.date.available2019-04-19T00:04:44Z-
dc.date.issued2019en_UK
dc.identifier.urihttp://hdl.handle.net/1893/29359-
dc.description.abstractUnderstanding why some problems are better solved by one algorithm rather than another is still an open problem, and the symmetric Travelling Salesperson Problem (TSP) is no exception. We apply three state-of-the-art heuristic solvers to a large set of TSP instances of varying structure and size, identifying which heuristics solve specific instances to optimality faster than others. The first two solvers considered are variants of the multi-trial Helsgaun's Lin-Kernighan Heuristic (a form of iterated local search), with each utilising a different form of Partition Crossover; the third solver is a genetic algorithm (GA) using Edge Assembly Crossover. Our results show that the GA with Edge Assembly Crossover is the best solver, shown to significantly outperform the other algorithms in 73% of the instances analysed. A comprehensive set of features for all instances is also extracted, and decision trees are used to identify main features which could best inform algorithm selection. The most prominent features identified a high proportion of instances where the GA with Edge Assembly Crossover performed significantly better when solving to optimality.en_UK
dc.language.isoenen_UK
dc.publisherSpringer International Publishingen_UK
dc.relationMcMenemy P, Veerapen N, Adair J & Ochoa G (2019) Rigorous Performance Analysis of State-of-the-Art TSP Heuristic Solvers. In: Liefooghe A & Paquete L (eds.) Evolutionary Computation in Combinatorial Optimization. Lecture Notes in Computer Science, 11452. EVOCOP 2019: European Conference on Evolutionary Computation in Combinatorial Optimization, Leipzig, Germany, 24.04.2019-26.04.2019. Cham, Switzerland: Springer International Publishing, pp. 99-114. https://doi.org/10.1007/978-3-030-16711-0_7en_UK
dc.relation.ispartofseriesLecture Notes in Computer Science, 11452en_UK
dc.relation.urihttp://hdl.handle.net/11667/127en_UK
dc.rightsThis is a post-peer-review, pre-copyedit version of a paper published in Liefooghe A & Paquete L (eds.) Evolutionary Computation in Combinatorial Optimization. Lecture Notes in Computer Science, 11452. EVOCOP 2019: European Conference on Evolutionary Computation in Combinatorial Optimization, Leipzig, Germany, 24.04.2019-26.04.2019. Cham, Switzerland: Springer International Publishing, pp. 99-114. The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-16711-0_7en_UK
dc.subjectTSPen_UK
dc.subjectAlgorithm selectionen_UK
dc.subjectEAXen_UK
dc.subjectGPXen_UK
dc.subjectPerformance analysisen_UK
dc.titleRigorous Performance Analysis of State-of-the-Art TSP Heuristic Solversen_UK
dc.typeConference Paperen_UK
dc.identifier.doi10.1007/978-3-030-16711-0_7en_UK
dc.citation.jtitleLecture Notes in Computer Science; Theory and Applications of Models of Computationen_UK
dc.citation.issn1611-3349en_UK
dc.citation.issn0302-9743en_UK
dc.citation.spage99en_UK
dc.citation.epage114en_UK
dc.citation.publicationstatusPublisheden_UK
dc.type.statusAM - Accepted Manuscripten_UK
dc.contributor.funderThe Leverhulme Trusten_UK
dc.contributor.funderEPSRC Engineering and Physical Sciences Research Councilen_UK
dc.author.emailpaul.mcmenemy@stir.ac.uken_UK
dc.citation.btitleEvolutionary Computation in Combinatorial Optimizationen_UK
dc.citation.conferencedates2019-04-24 - 2019-04-26en_UK
dc.citation.conferencelocationLeipzig, Germanyen_UK
dc.citation.conferencenameEVOCOP 2019: European Conference on Evolutionary Computation in Combinatorial Optimizationen_UK
dc.citation.date28/03/2019en_UK
dc.citation.isbn978-3-030-16710-3en_UK
dc.citation.isbn978-3-030-16711-0en_UK
dc.publisher.addressCham, Switzerlanden_UK
dc.contributor.affiliationComputing Scienceen_UK
dc.contributor.affiliationLille University of Science & Technology (University of Lille 1)en_UK
dc.contributor.affiliationComputing Scienceen_UK
dc.contributor.affiliationComputing Scienceen_UK
dc.identifier.scopusid2-s2.0-85064904823en_UK
dc.identifier.wtid1271273en_UK
dc.contributor.orcid0000-0002-5280-425Xen_UK
dc.contributor.orcid0000-0003-3699-1080en_UK
dc.contributor.orcid0000-0001-7649-5669en_UK
dc.date.accepted2019-02-08en_UK
dc.date.filedepositdate2019-04-18en_UK
dc.relation.funderprojectDAASE: Dynamic Adaptive Automated Software Engineeringen_UK
dc.relation.funderprojectThe Cartography of Computational Search Spacesen_UK
dc.relation.funderrefEP/J017515/1en_UK
dc.relation.funderrefRPG-2015-395en_UK
Appears in Collections:Computing Science and Mathematics Conference Papers and Proceedings

Files in This Item:
File Description SizeFormat 
McMenemy.pdfFulltext - Accepted Version3.73 MBAdobe PDFView/Open


This item is protected by original copyright



Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

If you believe that any material held in STORRE infringes copyright, please contact library@stir.ac.uk providing details and we will remove the Work from public display in STORRE and investigate your claim.