Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/28894
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dc.contributor.authorTinós, Renatoen_UK
dc.contributor.authorWhitley, Darrellen_UK
dc.contributor.authorOchoa, Gabrielaen_UK
dc.date.accessioned2019-03-05T01:03:03Z-
dc.date.available2019-03-05T01:03:03Z-
dc.date.issued2020-06-01en_UK
dc.identifier.urihttp://hdl.handle.net/1893/28894-
dc.description.abstractGeneralized Partition Crossover (GPX) is a deterministic recombination operator developed for the Traveling Salesman Problem. Partition crossover operators return the best of 2 k reachable offspring, where k is the number of recombining components. This paper introduces a new GPX2 operator, which finds more recombining components than GPX or Iterative Partial Transcription (IPT). We also show that GPX2 has O(n) runtime complexity, while also introducing new enhancements to reduce the execution time of GPX2. Finally, we experimentally demonstrate the efficiency of GPX2 when it is used to improve solutions found by multi-trial Lin-Kernighan-Helsgaum (LKH) algorithm. Significant improvements in performance are documented on large (n > 5000) and very large (n = 100, 000) instances of the Traveling Salesman Problem.en_UK
dc.language.isoenen_UK
dc.publisherMassachusetts Institute of Technology Press (MIT Press)en_UK
dc.relationTinós R, Whitley D & Ochoa G (2020) A New Generalized Partition Crossover for the Traveling Salesman Problem: Tunneling Between Local Optima. Evolutionary Computation, 28 (2), pp. 255-288. https://doi.org/10.1162/evco_a_00254en_UK
dc.rightsThis is is the author's final version of an article accepted for publication in Evolutionary Computation published by MIT Press. https://doi.org/10.1162/evco_a_00254en_UK
dc.rights.urihttps://storre.stir.ac.uk/STORREEndUserLicence.pdfen_UK
dc.subjectTraveling salesman problemen_UK
dc.subjectrecombination operatoren_UK
dc.subjectevolutionary combinatorial op- timizationen_UK
dc.titleA New Generalized Partition Crossover for the Traveling Salesman Problem: Tunneling Between Local Optimaen_UK
dc.typeJournal Articleen_UK
dc.identifier.doi10.1162/evco_a_00254en_UK
dc.identifier.pmid30900928en_UK
dc.citation.jtitleEvolutionary Computationen_UK
dc.citation.issn1530-9304en_UK
dc.citation.issn1063-6560en_UK
dc.citation.volume28en_UK
dc.citation.issue2en_UK
dc.citation.spage255en_UK
dc.citation.epage288en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusAM - Accepted Manuscripten_UK
dc.author.emailgabriela.ochoa@stir.ac.uken_UK
dc.citation.date22/03/2019en_UK
dc.contributor.affiliationFederal University of Sao Pauloen_UK
dc.contributor.affiliationColorado State Universityen_UK
dc.contributor.affiliationComputing Scienceen_UK
dc.identifier.isiWOS:000539231700004en_UK
dc.identifier.scopusid2-s2.0-85085905452en_UK
dc.identifier.wtid1237381en_UK
dc.contributor.orcid0000-0001-7649-5669en_UK
dc.date.accepted2019-02-15en_UK
dcterms.dateAccepted2019-02-15en_UK
dc.date.filedepositdate2019-03-04en_UK
rioxxterms.apcnot requireden_UK
rioxxterms.typeJournal Article/Reviewen_UK
rioxxterms.versionAMen_UK
local.rioxx.authorTinós, Renato|en_UK
local.rioxx.authorWhitley, Darrell|en_UK
local.rioxx.authorOchoa, Gabriela|0000-0001-7649-5669en_UK
local.rioxx.projectInternal Project|University of Stirling|https://isni.org/isni/0000000122484331en_UK
local.rioxx.freetoreaddate2019-03-04en_UK
local.rioxx.licencehttps://storre.stir.ac.uk/STORREEndUserLicence.pdf|2019-03-04|en_UK
local.rioxx.filenameGen_Partitition-crossover-ecj2019.pdfen_UK
local.rioxx.filecount1en_UK
local.rioxx.source1530-9304en_UK
Appears in Collections:Computing Science and Mathematics Journal Articles

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