Strategic Route Planning: An Adaptive BR-Heuristic for Multi-depot Logistics

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dc.contributor.affiliationCentro de Investigación en Gestión e Ingeniería de Producción
dc.contributor.authorEscoto-Gomar, Marc
dc.contributor.authorGuerrero, Antonies_ES
dc.contributor.authorMedina-Rodriguez, Veronica
dc.contributor.funderAGENCIA ESTATAL DE INVESTIGACIONes_ES
dc.date.accessioned2026-06-04T06:17:28Z
dc.date.available2026-06-04T06:17:28Z
dc.date.issued2025-01-31es_ES
dc.description.abstract[EN] The multiple traveling salesman problem (mTSP) is an extension of the well-known traveling salesman problem (TSP), requiring multiple agents to visit a set of nodes and return to their respective depot. This problem finds wide-ranging applications in robotics, transportation and networking, among other domains. Moreover, it can be readily extended to a vehicle routing problem (VRP) by introducing extra constraints. This article presents a hybrid method for addressing the multi-depot closed path mTSP by integrating a bias-randomized heuristic with iterative local search (ILS). Furthermore, this algorithm is enhanced with a self-tuning mechanism, eliminating the need for timeconsuming fine-tuning processes. The results provided by this algorithm with a different number of depots are analyzed.es_ES
dc.description.accrualMethodSes_ES
dc.description.bibliographicCitationEscoto-Gomar, Marc; Guerrero, A.; Medina-Rodriguez, Veronica (2025). Strategic Route Planning: An Adaptive BR-Heuristic for Multi-depot Logistics. Lecture Notes in Computer Science. 14779:372-382. https://doi.org/10.1007/978-3-031-78241-1_34es_ES
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dc.description.sponsorshipThis work has been partially supported by the Spanish Ministry of Science and Innovation (PID2022-138860NB-I00 and RED2022-134703-T).es_ES
dc.description.upvformatpfin382es_ES
dc.description.upvformatpinicio372es_ES
dc.description.volume14779es_ES
dc.identifier.doi10.1007/978-3-031-78241-1_34es_ES
dc.identifier.issn0302-9743es_ES
dc.identifier.urihttps://riunet.upv.es/handle/10251/235792
dc.languageIngléses_ES
dc.publisherSpringer-Verlages_ES
dc.relation.ispartofLecture Notes in Computer Sciencees_ES
dc.relation.pasarelaS\584151es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2022-138860NB-I00/ES/INTELIGENCIA ARTIFICIAL E INTERNET DE LAS COSAS PARA OPTIMIZAR EL CONSUMO ENERGETICO EN EL TRANSPORTE CON VEHICULOS ELECTRICOS/es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI//RED2022-134703-T//Red Española en Transporte, Inteligencia Artificial, y Analítica de Datos/es_ES
dc.relation.publisherversionhttps://doi.org/10.1007/978-3-031-78241-1_34es_ES
dc.rightsReserva de todos los derechoses_ES
dc.rights.accessRightsAbiertoes_ES
dc.subjectMultiple traveling salesman problemes_ES
dc.subjectBias-randomizatioes_ES
dc.titleStrategic Route Planning: An Adaptive BR-Heuristic for Multi-depot Logisticses_ES
dc.typeArtículoes_ES
dc.type.versioninfo:eu-repo/semantics/publishedVersiones_ES
dspace.entity.typePublication
person.identifier733538
person.identifier821228
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relation.isAuthorOfPublication01eb4a1a-bbb4-49a8-b3e7-9c391148043c
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