Publication:
A multi-start granular skewed variable neighborhood tabu search for the roaming salesman problem

dc.contributor.coauthorShahmanzari, Masoud
dc.contributor.departmentDepartment of Business Administration
dc.contributor.kuauthorAksen, Deniz
dc.contributor.kuprofileFaculty Member
dc.contributor.yokid40308
dc.date.accessioned2024-11-09T22:59:02Z
dc.date.issued2021
dc.description.abstractThis paper presents a novel hybrid metaheuristic algorithm for the Roaming Salesman Problem (RSP), called Multi-Start Granular Skewed Variable Neighborhood Tabu Search (MS-GSVNTS). The objective in RSP is to design daily tours for a traveling campaigner who collects rewards from activities in cities during a fixed planning horizon. RSP exhibits a number of exclusive features: It is selective which implies that not every node needs a visit. The rewards of cities are time-dependent. Daily tours can be either an open or a closed tour which implies the absence of a fixed depot. Instead, there is a campaign base that is to be attended frequently. Multiple visits are allowed for certain cities. The proposed method MS-GSVNTS is tested on 45 real-life instances from Turkey which are built with actual travel distances and times and on 10 large scale instances. Computational results suggest that MS-GSVNTS is superior to the existing solution methods developed for RSP. It produces 50 best known solutions including 18 ties and 32 new ones. The performance of MS-GSVNTS can be attributed to its multi-start feature, rich neighborhood structures, skewed moves, and granular neighborhoods.
dc.description.indexedbyWoS
dc.description.indexedbyScopus
dc.description.openaccessNO
dc.description.publisherscopeInternational
dc.description.sponsoredbyTubitakEuN/A
dc.description.volume102
dc.identifier.doi10.1016/j.asoc.2020.107024
dc.identifier.eissn1872-9681
dc.identifier.issn1568-4946
dc.identifier.scopus2-s2.0-85099253826
dc.identifier.urihttp://dx.doi.org/10.1016/j.asoc.2020.107024
dc.identifier.urihttps://hdl.handle.net/20.500.14288/7825
dc.identifier.wos632599300001
dc.keywordsRoaming salesman problem
dc.keywordsCampaign planning
dc.keywordsElection logistics
dc.keywordsMetaheuristics
dc.keywordsVariable neighborhood search vehicle-routing problem
dc.keywordsTeam orienteering problem
dc.keywordsCut algorithm
dc.keywordsSolve
dc.keywordsDelivery
dc.keywordsPickup
dc.languageEnglish
dc.publisherElsevier
dc.sourceApplied Soft Computing
dc.subjectComputer science
dc.subjectArtificial intelligence
dc.subjectComputer science
dc.subjectInterdisciplinary applications
dc.titleA multi-start granular skewed variable neighborhood tabu search for the roaming salesman problem
dc.typeJournal Article
dspace.entity.typePublication
local.contributor.authorid0000-0003-1734-2042
local.contributor.kuauthorAksen, Deniz
local.publication.orgunit1College of Administrative Sciences and Economics
local.publication.orgunit2Department of Business Administration
relation.isOrgUnitOfPublicationca286af4-45fd-463c-a264-5b47d5caf520
relation.isOrgUnitOfPublication.latestForDiscoveryca286af4-45fd-463c-a264-5b47d5caf520

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