期刊
SWARM AND EVOLUTIONARY COMPUTATION
卷 38, 期 -, 页码 64-78出版社
ELSEVIER
DOI: 10.1016/j.swevo.2017.06.003
关键词
Migrating birds optimization; Meta-heuristics; Lot-streaming; Flow shop; Harmony search
资金
- Shanghai Key Laboratory of Power Station Automation Technology
- National Natural Science Foundation of China [51575212, 61174187]
Lot-streaming is an effective technology to enhance the production efficiency by splitting a job or a lot into several sublots. It is commonly assumed that lot-splitting (i.e. job-splitting) is specified in advance and fixed during the optimization procedure in recent studies on lot-streaming flow shop scheduling problems. In many real-world production processes, however, it is not easy to determine the optimal lot-splitting beforehand. Therefore, in this paper we consider an integrated lot-streaming flow shop scheduling problem in which lot splitting and job scheduling are needed to be optimized simultaneously. We provide a mathematical model for the problem and present an improved migrating birds optimization (IMMBO) to minimize the maximum completion time or makespan. In the IMMBO algorithm, a harmony search based scheme is designed to construct neighborhood of solutions, which makes good use of optimization information from the population and can tune the search scope adaptively. Moreover, a leaping mechanism is introduced to avoid being trapped in the local optimum. Extensive numerical simulations are conducted and comparisons with other state-of-theart algorithms verify the effectiveness of the proposed IMMBO algorithm.
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