Hybrid metaheuristics to solve a multi-product two-stage capacitated facility location problem

dc.contributor.authorChaves, Antonio Augusto [UNIFESP]
dc.contributor.authorMauri, Geraldo Regis
dc.contributor.authorBiajoli, Fabricio Lacerda [UNIFESP]
dc.contributor.authorRabello, Rômulo Louzada
dc.contributor.authorRibeiro, Glaydston Mattos
dc.contributor.authorLorena, Luiz Antônio Nogueira [UNIFESP]
dc.contributor.authorLatteshttp://lattes.cnpq.br/4973949421738244
dc.date.accessioned2024-05-24T13:45:54Z
dc.date.available2024-05-24T13:45:54Z
dc.date.issued2021
dc.description.abstractThis paper presents two hybrid metaheuristics to solve a multi-product two-stage capacitated facility location prob- lem (MP-TSCFLP). In this problem, a set of different products must be transported from a set of plants to a set of intermediate depots (first stage) and from these depots to a set of customers (second stage). The objective is to minimize the cost related to open plants and depots plus the cost for transporting the products from the plants until the customers satisfying demand and capacity constraints. Recently, the methods Clustering Search (CS) and Biased Random-Key Genetic Algorithm (BRKGA) were successfully applied to solve a single-product problem (SP-TSCFLP). Therefore, in this paper we propose adaptations and implementations of these methods for handling with a multi-product approach. To the best of our knowledge, CS and BRKGA presented the best results for the SP-TSCFLP and both have not yet been applied to solve the problem with multiple products. Four sets of large- sized instances with different characteristics are proposed and computational experiments compare the obtained results to those from a commercial solver.
dc.identifierhttp://dx.doi.org/ 10.1111/itor.12930
dc.identifier.doi10.1111/itor.12930
dc.identifier.urihttps://hdl.handle.net/11600/71140
dc.languageeng
dc.publisherWiley
dc.relation.ispartofInternational Transactions In Operational Research
dc.rightsAcesso restrito
dc.subjectClustering Search
dc.subjectBiased Random-Key Genetic Algorithm
dc.subjectTwo-Stage Capacitated Facility Location
dc.subjectMulti- Product.
dc.titleHybrid metaheuristics to solve a multi-product two-stage capacitated facility location problem
dc.typeArtigo
unifesp.campusInstituto de Ciência e Tecnologia (ICT)
unifesp.departamentoCiência e Tecnologia
unifesp.graduacaoNão se aplica
unifesp.graduateProgramCiência da Computação
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