Parallel genetic algorithm approaches applied to solve a synchronized and integrated lot sizing and scheduling problem

Authors:
Claudio Fabiano Motta Toledo;Lucas de Oliveira;Renato Resende Ribeiro de Oliveira;Marluce Rodrigues Pereira
Affiliations:
Universidade Federal de Lavras, Lavras, MG;Universidade Federal de Lavras, Lavras, MG;Universidade Federal de Lavras, Lavras, MG;Universidade Federal de Lavras, Lavras, MG
Venue:
Proceedings of the 2010 ACM Symposium on Applied Computing
Year:
2010

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Abstract

This paper evaluates different parallel approaches for multipopulation genetic algorithm. These approaches are applied to solve a synchronized and integrated lot sizing and scheduling problem. In this problem, the challenge is to simultaneously determine lot sizing and scheduling for raw materials in tanks and products in lines. First, the parallel algorithms are designed to be executed using a multicore server. The best approach is also executed by duo core computers using MPI. A set of real-world instances found in the literature are solved. Also, a new set of instances is proposed. The speedups improvements are showed as well as the quality of final solutions found.