Please use this identifier to cite or link to this item:
http://acervodigital.unesp.br/handle/11449/76310
- Title:
- Genetic algorithm, MIP and improvement heuristic applied to the MLCLP with backlogging
- Universidade de São Paulo (USP)
- Universidade Estadual Paulista (UNESP)
- 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.
- 21-Aug-2013
- 2013 IEEE Congress on Evolutionary Computation, CEC 2013, p. 1483-1490.
- 1483-1490
- 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
- http://dx.doi.org/10.1109/CEC.2013.6557738
- Acesso restrito
- outro
- http://repositorio.unesp.br/handle/11449/76310
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