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dc.contributor.authorLacovic, Elvira
dc.contributor.authorChica Serrano, Manuel
dc.contributor.authorDamas Arroyo, Sergio
dc.contributor.authorBautista Valhondo, Joaquín
dc.contributor.authorCordón García, Oscar
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Organització d'Empreses
dc.date.accessioned2015-02-06T12:30:58Z
dc.date.available2015-02-06T12:30:58Z
dc.date.created2015
dc.date.issued2015
dc.identifier.citationLacovic, E. [et al.]. A refined GRASP algorithm for the extended car sequencing problem. A: Congreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados. "Actas del X Congreso español sobre metaheurísticas, algoritmos evolutivos y bioinspirados: MAEB 2015: Merida-Almendralejo, 4, 5 y 6 de febrero de 2015". Mérida, Cáceres: 2015, p. 1-8.
dc.identifier.urihttp://hdl.handle.net/2117/26250
dc.description.abstractIn this study, we investigate the performance of GRASP (Greedy Randomized Adaptive Search Procedure) mataheuristic that has been used for solving extended optimization version of CSP (Car Sequencing Problem) with respect to different parameters and proposed modifications for the algorithm. While maximum appearance frequency of option in segment is usually a hard constraint, in this study we treat all capacity constraints as soft constraints by giving them same priority when evaluating candidates for the position in the sequence, in order to achieve more balanced sequences as initial solutions for the local improvement phase. The main disadvantage of the described greedy algorithm using static value of α GRASP parameter is that it uses all the good options at the beginning of the sequence, leaving the worse options for the last part of the sequence. Based on this, changing the starting position of the sequence and order of moves for the local search has been investigated. Results show that the starting position of the sequence for the local search matters and taking into account changing the starting position of the sequence for exploring moves for the local improvement can lead to better solutions.
dc.format.extent8 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Economia i organització d'empreses
dc.subject.lcshHeuristic algorithms
dc.subject.otherar sequencing problem
dc.subject.otherGRASP
dc.subject.otherMe- taheuristics
dc.titleA refined GRASP algorithm for the extended car sequencing problem
dc.typeConference report
dc.subject.lemacHeurística
dc.subject.lemacGRASP (Fitxer informàtic)
dc.subject.lemacProducció -- Sistemes
dc.contributor.groupUniversitat Politècnica de Catalunya. OPE - Organització de la Producció i d'Empresa (aspectes tècnics, jurídics i econòmics en Producció)
dc.rights.accessOpen Access
local.identifier.drac15416000
dc.description.versionPostprint (published version)
local.citation.authorLacovic, E.; Chica, M.; Damas, S.; Bautista, J.; Cordón, O.
local.citation.contributorCongreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados
local.citation.pubplaceMérida, Cáceres
local.citation.publicationNameActas del X Congreso español sobre metaheurísticas, algoritmos evolutivos y bioinspirados: MAEB 2015: Merida-Almendralejo, 4, 5 y 6 de febrero de 2015
local.citation.startingPage1
local.citation.endingPage8


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