METAHEURISTIC ALGORITHMS FOR FLEXIBLE FLOW SHOP SCHEDULING PROBLEM WITH UNRELATED PARALLEL MACHINES
DOI:
https://doi.org/10.23055/ijietap.2019.26.6.3376Keywords:
flexible flow shop, makespan, genetic algorithm, Particle Swarm Optimization, mathematical modelAbstract
Flexible flow shop scheduling problems (FFS) with multiple unrelated machines are common manufacturing environments in many industries, such as the semiconductor, steel, ceramic tile and lead frame industries. This work proposes an improved mathematical model to solve the problem with minimum makespan objective. Since the research problem is shown to be NP-hard, two versions of the PSO, two versions of the GA, and a Hybrid PSO-GA (HPG) algorithm, are applied to solve the problem, approximately. The proposed meta-heuristic algorithms are tested on some test problems, inspired by Carlier and Néron’s benchmark problems. Computational results show that all the proposed algorithms can efficiently and effectively minimize the makespan, and the HPG is the most effective.Published
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