Genetic algorithm, MIP and improvement heuristic applied to the MLCLP with backlogging

Trabalho apresentado em evento

Fecha

2013-08-21

Registro en:

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

http://repositorioslatinoamericanos.uchile.cl/handle/2250/3925201

Autor

Universidade de São Paulo (USP)

Universidade Estadual Paulista (Unesp)

Institución

Universidade Paulista Júlio de Mesquita Filho (Brasil)

Resumen

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.

Materias

Capacitated lot sizing problem

Computational results

Hybrid Meta-heuristic

Lot sizing

Mixed-Integer Programming

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