期刊
COMPUTERS IN INDUSTRY
卷 81, 期 -, 页码 82-95出版社
ELSEVIER
DOI: 10.1016/j.compind.2015.10.001
关键词
Dynamic scheduling; Energy consumption; Flexible flow shop; Particle swarm optimization
资金
- 7th European Community Framework Programme [294931]
- Spanish Government [TIN2013-46511-C2-1-P]
- National Natural Science Foundation of China [51175262]
- Jiangsu Province Science Foundation for Excellent Youths [BK2012032]
Due to increasing energy requirements and associated environmental impacts, nowadays manufacturing companies are facing the emergent challenges to meet the demand of sustainable manufacturing. Most existing research on reducing energy consumption in production scheduling problems has focused on static scheduling models. However, there exist many unexpected disruptions like new job arrivals and machine breakdown in a real-world production scheduling. In this paper, it is proposed anapproach to address the dynamic scheduling problem reducing energy consumption and makespan for a flexible flow shop scheduling. Since the problem is strongly NP-hard, a novel algorithm based on an improved particle swarm optimization is adopted to search for the Pareto optimal solution in dynamic flexible flow shop scheduling problems. Finally, numerical experiments are carried out to evaluate the performance and efficiency of the proposed approach. (C) 2015 Elsevier B.V. All rights reserved.
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