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dc.contributor.authorDauer, Armando Teles-
dc.contributor.authorPrata, Bruno de Athayde-
dc.date.accessioned2023-04-27T11:20:39Z-
dc.date.available2023-04-27T11:20:39Z-
dc.date.issued2021-
dc.identifier.citationDAUER, Armando Teles; PRATA, Bruno de Athayde. Variable fixing heuristics for solving multiple depot vehicle scheduling problem with heterogeneous fleet and time windows. Optimization Letters, [S. l.], v. 15, p. 153-170, 2021.pt_BR
dc.identifier.issn1862-4480-
dc.identifier.urihttp://www.repositorio.ufc.br/handle/riufc/71925-
dc.description.abstractThis paper aims at presenting the multiple depot vehicle scheduling problem with heterogeneous fleet and time windows (MDHFVSP-TW). We used a time-space network (TSN) to perform the modeling of MDHFVSP-TW, along with two methodologies to reduce its size and, therefore, its complexity. Along with size reduction methods, a mixed integer programming (MIP) heuristic with variable fixation was presented. Its operation is based on the use of the solution for this problem with relaxed variables as a basis for the removal of arcs from the problem, reducing its size and enabling its resolution in reasonable computational time. Extensive tests were performed for a collection of randomly generated instances. Subsequently, a case study arising from a real instance from a Brazilian city is presented. The computational results showed that the proposed heuristic and size reduction methods obtained good performance, providing high-quality solutions in an adequate computational time.pt_BR
dc.language.isoenpt_BR
dc.publisherOptimization Letterspt_BR
dc.rightsAcesso Abertopt_BR
dc.subjectCombinatorial optimizationpt_BR
dc.subjectPublic transport systemspt_BR
dc.subjectMixed integer linear programmingpt_BR
dc.subjectMachine learningpt_BR
dc.titleVariable fixing heuristics for solving multiple depot vehicle scheduling problem with heterogeneous fleet and time windowspt_BR
dc.typeArtigo de Periódicopt_BR
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