4.5 Article

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

期刊

COMPUTERS & OPERATIONS RESEARCH
卷 40, 期 4, 页码 910-919

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cor.2012.11.002

关键词

Genetic algorithms; Hybridization; Fix and optimize; Lot sizing; Backlogging; Multi-level

资金

  1. Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP) [2011/15534-5, 2011/15581-3, 2010/10133-0]
  2. Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP) [11/15581-3] Funding Source: FAPESP

向作者/读者索取更多资源

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. (C) 2012 Elsevier Ltd. All rights reserved.

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