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

被引：47

作者：

Motta Toledo, Claudio Fabiano ^{[1
]}

Ribeiro de Oliveira, Renato Resende ^{[2
]}

Franca, Paulo Morelato ^{[3
]}

机构：

[1] Univ Sao Paulo, Inst Math & Comp Sci, BR-05508 Sao Paulo, Brazil

[2] Univ Fed Lavras, Dept Comp Sci, Lavras, MG, Brazil

[3] Univ Estadual Paulista, Dept Math & Comp, Sao Paulo, Brazil

来源：

COMPUTERS & OPERATIONS RESEARCH | 2013年 / 40卷 / 04期

基金：

巴西圣保罗研究基金会;

关键词：

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

D O I：

10.1016/j.cor.2012.11.002

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

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.

引用

页码：910 / 919

页数：10

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