Title :
Genetic algorithm, MIP and improvement heuristic applied to the MLCLP with backlogging
Author :
Toledo, C.F.M. ; Hossomi, Marcelo Y. B. ; da Silva Arantes, Marcio ; Morelato Franca, Paulo
Author_Institution :
Inst. of Math. & Comput. Sci., Univ. of Sao Paulo, Sao Carlos, Brazil
Abstract :
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.
Keywords :
genetic algorithms; integer programming; lot sizing; MIP; MLCLP-with-backlogging; MLCLSPB; benchmark instances; genetic algorithm; heuristics; mixed-integer programming models; multilevel capacitated lot sizing problem-with-backlogging; Computational modeling; Genetic algorithms; Lot sizing; Mathematical model; Programming; Sociology; Statistics; genetic algorithm; hybrid metaheuristic; lot-sizing; multi-level;
Conference_Titel :
Evolutionary Computation (CEC), 2013 IEEE Congress on
Conference_Location :
Cancun
Print_ISBN :
978-1-4799-0453-2
Electronic_ISBN :
978-1-4799-0452-5
DOI :
10.1109/CEC.2013.6557738
