Métodos de geração de colunas para problemas de atribuição

dc.contributorUniversidade Estadual Paulista (UNESP)
dc.contributorLaboratório Associado de Computação e Matemática Aplicada
dc.date.accessioned2022-04-29T08:47:41Z
dc.date.accessioned2022-12-20T03:20:35Z
dc.date.available2022-04-29T08:47:41Z
dc.date.available2022-12-20T03:20:35Z
dc.date.created2022-04-29T08:47:41Z
dc.date.issued2007-01-01
dc.identifierProducao, v. 17, n. 1, p. 071-083, 2007.
dc.identifier1980-5411
dc.identifier0103-6513
dc.identifierhttp://hdl.handle.net/11449/231816
dc.identifier2-s2.0-34648823588
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/5411950
dc.description.abstractThis work presents column generation methods for two important assignment problems: the Generalized Assignment Problem (GAP) and the problem of assigning calls to switches in cellular mobile networks (PAGS) G4P is one of the most representative combinatorial optimisation problems and can be stated as the problem of optimising the assignment of n jobs to m agents, such that each job is assigned to exactly one agent and the resource capacity of each agent is not violated. PACS consists of determining a cell assignment pattern which minimizes cabling costs between a ceil and a switch and transfer costs between cells assigned to different switches, while respecting certain constraints, especially those related to limited switch's capacity. The traditional column generation process is compared with the proposed algorithms that combine the column generation and lagrangean/surrogate reladon. Computational experiments are presented in order to confirm the effectiveness of the proposed algorithms.
dc.languagepor
dc.relationProducao
dc.sourceScopus
dc.subjectAssignment problems
dc.subjectColumn generation
dc.subjectCombinatorial optimization
dc.subjectLagrangean/surrogate relaxation
dc.titleColumn generaton methods assignment problems
dc.titleMétodos de geração de colunas para problemas de atribuição
dc.typeArtículos de revistas


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