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

Authors:
Claudio Fabiano Motta Toledo;Renato Resende Ribeiro De Oliveira;Paulo Morelato FrançA
Affiliations:
University of São Paulo, Institute of Mathematics and Computer Science, Brazil;Federal University of Lavras, Department of Computer Science, Brazil;UNESP - Department of Mathematics and Computing, Brazil
Venue:
Computers and Operations Research
Year:
2013

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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.