期刊
IEEE TRANSACTIONS ON FUZZY SYSTEMS
卷 27, 期 5, 页码 1008-1022出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TFUZZ.2019.2895562
关键词
Cooperative coevolution algorithm; fuzzy scheduling; flexible job shop scheduling
资金
- National Natural Science Foundation of China [61572100]
Flexible scheduling is one of the most significant core techniques for intelligent manufacturing systems. Realization of an optimized schedule through flexible resources assignment is critical to the application and popularization of flexible scheduling, especially in uncertain manufacturing environments. In this paper, we consider flexible job shop scheduling with uncertain processing time represented by fuzzy numbers, which is named fuzzy flexible job shop scheduling. We propose an effective hybrid cooperative coevolution algorithm (hCEA) for the minimization of fuzzy makespan. The hCEA combines particle swarm optimization with the genetic algorithm to improve the convergence ability. A parameter self-adaptive strategy is applied to the problems with different scale effectively as well. Five benchmarks and three large-scale problems with fuzzy processing time are adopted to test the hCEA. Computational results show that the hCEA performs better than the existing methods from the literature.
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