Journal
EXPERT SYSTEMS WITH APPLICATIONS
Volume 124, Issue -, Pages 309-324Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2019.01.062
Keywords
Scheduling; Flowshop; Artificial bee colony; Scatter search; Iterated local search; Iterated greedy
Categories
Funding
- National Science Foundation of China [51575212, 51775216, 61876169, 61873328]
- National Natural Science Fund for Distinguished Young Scholars of China [51825502, 61525304]
- Shanghai Key Laboratory of Power station Automation Technology
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Distributed permutation flowshop scheduling problem (DPFSP) has become a very active research area in recent years. However, minimizing total fiowtime in DPFSP, a very relevant and meaningful objective for today's dynamic manufacturing environment, has not captured much attention so far. In this paper, we address the DPFSP with total flowtime criterion. To suit the needs of different CPU time demands and solution quality, we present three constructive heuristics and four metaheuristics. The constructive heuristics are based on the well-known LR and NEH heuristics. The metaheuristics are based on the high-performing frameworks of discrete artificial bee colony, scatter search, iterated local search, and iterated greedy, which have been applied with great success to closely related scheduling problems. We explore the problem-specific knowledge and accelerations to evaluate neighboring solutions for the considered problem. We introduce advanced and effective technologies like a referenced local search, a strategy to escape from local optima, and an enhanced intensive search method for the presented metaheuristics. A comprehensive computational campaign against the closely related and well performing algorithms in the literature is carried out. The results show that both the presented constructive heuristics and meta heuristics are very effective for solving the DPFSP with total fiowtime criterion. (C) 2019 The Authors. Published by Elsevier Ltd.
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