期刊
APPLIED MATHEMATICAL MODELLING
卷 38, 期 9-10, 页码 2490-2504出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.apm.2013.10.061
关键词
Hybrid flow shop scheduling; Multi-objective optimization; Sequence-dependent setup time; Stochastic modeling; Metaheuristic algorithms
This paper studies the scheduling problem in hybrid flow shop (HFS) environment. The sequence dependent family setup time (SDFST) is concerned with minimization of makespan and total tardiness. Production environments in real world include innumerable cases of uncertainty and stochasticity of events and a suitable scheduling model should consider them. Hence, in this paper, due date is assumed to be uncertain and its data follow a normal distribution. Since the proposed problem is NP-hard, two metaheuristic algorithms are presented based on genetic algorithm, namely: Non-dominated Sorting Genetic Algorithm (NSGAII) and Multi Objective Genetic Algorithm (MOGA). The quantitative and qualitative results of these two algorithms have been compared in different dimensions with multi phase genetic algorithm (MPGA) used in literature review. Experimental results indicate that the NSGAII performs very well when compared against MOGA and MPGA in a considerably shorter time. (C) 2013 Elsevier Inc. All rights reserved.
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