Genetic Algorithms for the Picker Routing Problem in Multi-block Warehouses

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dc.contributor.affiliationCano, J.A., Universidad de Medellín, Carrera 87 # 30-65, Medellín, Colombia
dc.contributor.affiliationCorrea-Espinal, A.A., Universidad Nacional de Colombia, Carrera 80 # 65-223, Medellín, Colombia
dc.contributor.affiliationGómez-Montoya, R.A., ESACS – Escuela Superior en Administración de Cadena de Suministro, Calle 4 # 18-55, Medellín, Colombia
dc.contributor.affiliationCortés, P., Universidad de Sevilla, Camino de los Descubrimientos s/n, Sevilla, 41092, Spain
dc.contributor.authorCano J.A.
dc.contributor.authorCorrea-Espinal A.A.
dc.contributor.authorGómez-Montoya R.A.
dc.contributor.authorCortés P.
dc.date2019
dc.date.accessioned2021-02-05T14:59:13Z
dc.date.available2021-02-05T14:59:13Z
dc.descriptionThis article presents a genetic algorithm (GA) to solve the picker routing problem in multiple-block warehouses in order to minimize the traveled distance. The GA uses survival, crossover, immigration, and mutation operators, and is complemented by a local search heuristic. The genetic algorithm provides average distance savings of 13.9% when compared with s-shape strategy, and distance savings of 23.3% when compared with the GA with the aisle-by-aisle policy. We concluded that the GA performs better as the number of blocks increases, and as the percentage of picking locations to visit decreases. © 2019, Springer Nature Switzerland AG.
dc.identifier.doi10.1007/978-3-030-20485-3_24
dc.identifier.isbn9783030204846
dc.identifier.issn18651348
dc.identifier.urihttp://hdl.handle.net/11407/6081
dc.language.isoeng
dc.publisherSpringer Verlagspa
dc.publisher.facultyFacultad de Ciencias Económicas y Administrativasspa
dc.publisher.programAdministración de Empresasspa
dc.relation.citationendpage322
dc.relation.citationstartpage313
dc.relation.citationvolume353
dc.relation.isversionofhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85068139598&doi=10.1007%2f978-3-030-20485-3_24&partnerID=40&md5=329ec9d2a5d26fb301d435f9ad3a8114
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dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.sourceLecture Notes in Business Information Processing
dc.subjectArtificial intelligencespa
dc.subjectGenetic algorithmspa
dc.subjectMulti-block warehousespa
dc.subjectOrder pickingspa
dc.subjectPicker routingspa
dc.subjectWarehouse managementspa
dc.subject.proposalArtificial intelligenceeng
dc.subject.proposalHeuristic algorithmseng
dc.subject.proposalInformation systemseng
dc.subject.proposalInformation useeng
dc.subject.proposalRouting algorithmseng
dc.subject.proposalWarehouseseng
dc.subject.proposalAverage Distanceeng
dc.subject.proposalLocal search heuristicseng
dc.subject.proposalMulti blockseng
dc.subject.proposalMutation operatorseng
dc.subject.proposalNumber of blockseng
dc.subject.proposalOrder pickingeng
dc.subject.proposalPicker routingeng
dc.subject.proposalWarehouse managementeng
dc.subject.proposalGenetic algorithmseng
dc.titleGenetic Algorithms for the Picker Routing Problem in Multi-block Warehouses
dc.typeConference Paper
dc.type.driverinfo:eu-repo/semantics/other
dc.type.versioninfo:eu-repo/semantics/publishedVersion

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