A hybrid multi-population genetic algorithm applied to solve the multi-level capacitated lot sizing problem with backlogging


Autoria(s): Toledo, Claudio Fabiano Motta; De Oliveira, Renato Resende Ribeiro; Morelato França, Paulo
Contribuinte(s)

Universidade Estadual Paulista (UNESP)

Data(s)

27/05/2014

27/05/2014

01/04/2013

Resumo

The present paper proposes a new hybrid multi-population genetic algorithm (HMPGA) as an approach to solve the multi-level capacitated lot sizing problem with backlogging. This method combines a multi-population based metaheuristic using fix-and-optimize heuristic and mathematical programming techniques. A total of four test sets from the MULTILSB (Multi-Item Lot-Sizing with Backlogging) library are solved and the results are compared with those reached by two other methods recently published. The results have shown that HMPGA had a better performance for most of the test sets solved, specially when longer computing time is given. © 2012 Elsevier Ltd.

Formato

910-919

Identificador

http://dx.doi.org/10.1016/j.cor.2012.11.002

Computers and Operations Research, v. 40, n. 4, p. 910-919, 2013.

0305-0548

http://hdl.handle.net/11449/74919

10.1016/j.cor.2012.11.002

WOS:000314483400002

2-s2.0-84870952214

Idioma(s)

eng

Relação

Computers and Operations Research

Direitos

closedAccess

Palavras-Chave #Backlogging #Fix and optimize #Genetic algorithms #Hybridization #Lot sizing #Multi-level #Heuristic methods #Mathematical programming
Tipo

info:eu-repo/semantics/article