期刊
COMPUTERS & INDUSTRIAL ENGINEERING
卷 124, 期 -, 页码 276-292出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cie.2018.07.023
关键词
NSGA-III; MOPSO; Assembly flow shop; Multi-objectives
Two-stage assembly flow shops are integral part of several manufacturing systems such as computer and engine manufacturing lines. This paper explores three objectives of makespan, total tardiness, and total completion times for two-stage assembly flow shop with release time. To the best of our knowledge, these performance measures have not been addressed simultaneously in assembly flow shops. We derive polynomial optimal solutions for special cases of this problem with a single objective and then develop heuristics with promising starting solutions for the multi-objective case. Due to NP-hardness of the problem, we apply a customized reference-based Non-dominated Sorting Genetic Algorithm (NSGA-III) and Multi-Objective Particle Swarm Optimization (MOPSO) as solution procedures. Finally, we present extensive computational analysis to compare the performance of employed heuristic and metaheuristics on randomly generated instances. Results show that both NSGA-III and MOPSO generate competitive solutions for the presented problem. However, NSGA-III generates significantly better results than MOPSO based on one of the three performance metrics.
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