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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/74919
Title: 
A hybrid multi-population genetic algorithm applied to solve the multi-level capacitated lot sizing problem with backlogging
Author(s): 
Institution: 
  • Universidade de São Paulo (USP)
  • Federal University of Lavras
  • Universidade Estadual Paulista (UNESP)
ISSN: 
0305-0548
Abstract: 
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.
Issue Date: 
1-Apr-2013
Citation: 
Computers and Operations Research, v. 40, n. 4, p. 910-919, 2013.
Time Duration: 
910-919
Keywords: 
  • Backlogging
  • Fix and optimize
  • Genetic algorithms
  • Hybridization
  • Lot sizing
  • Multi-level
  • Heuristic methods
  • Mathematical programming
Source: 
http://dx.doi.org/10.1016/j.cor.2012.11.002
URI: 
Access Rights: 
Acesso restrito
Type: 
outro
Source:
http://repositorio.unesp.br/handle/11449/74919
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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