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

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 compa...

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Bibliographic Details
Main Authors: Toledo, Claudio F. M., Hossomi, Marcelo Y. B., da Silva Arantes, Marcio, Morelato Franca, Paulo
Format: Conference Proceeding
Language:English
Subjects:
Computational modeling
genetic algorithm
Genetic algorithms
hybrid metaheuristic
Lot sizing
Mathematical model
multi-level
Programming
Sociology
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Summary: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.
ISSN:1089-778X
1941-0026
DOI:10.1109/CEC.2013.6557738