Genetic algorithm, MIP and improvement heuristic applied to the MLCLP with backlogging
| Contribuinte(s) |
Universidade Estadual Paulista (UNESP) |
|---|---|
| Data(s) |
27/05/2014
27/05/2014
21/08/2013
|
| Resumo |
The present paper solves the multi-level capacitated lot sizing problem with backlogging (MLCLSPB) combining a genetic algorithm with the solution of mixed-integer programming models and the improvement heuristic fix and optimize. This approach is evaluated over sets of benchmark instances and compared to methods from literature. Computational results indicate competitive results applying the proposed method when compared with other literature approaches. © 2013 IEEE. |
| Formato |
1483-1490 |
| Identificador |
http://dx.doi.org/10.1109/CEC.2013.6557738 2013 IEEE Congress on Evolutionary Computation, CEC 2013, p. 1483-1490. http://hdl.handle.net/11449/76310 10.1109/CEC.2013.6557738 2-s2.0-84881575854 |
| Idioma(s) |
eng |
| Relação |
2013 IEEE Congress on Evolutionary Computation, CEC 2013 |
| Direitos |
closedAccess |
| Palavras-Chave | #genetic algorithm #hybrid metaheuristic #lot-sizing #multi-level #Capacitated lot sizing problem #Computational results #Hybrid Meta-heuristic #Lot sizing #Mixed-Integer Programming #Benchmarking #Heuristic methods #Integer programming #Genetic algorithms |
| Tipo |
info:eu-repo/semantics/conferencePaper |
