期刊
JOURNAL OF INTELLIGENT MANUFACTURING
卷 28, 期 8, 页码 1961-1972出版社
SPRINGER
DOI: 10.1007/s10845-015-1082-0
关键词
Particle swarm optimization; Simulated annealing; Dual-resource constraint; Resource flexibility
资金
- National Natural Science Foundation of China (NSFC) [61379123]
- National Key Technology R&D Program in the 12th Five Year Plan of China [2012BAD10B01]
In this paper, a novel hybrid discrete particle swarm optimization algorithm is proposed to solve the dual-resource constrained job shop scheduling problem with resource flexibility. Particles are represented based on a three-dimension chromosome coding scheme of operation sequence and resources allocation. Firstly, a mixed population initialization method is used for the particles. Then a discrete particle swarm optimization is designed as the global search process by taking the dual-resources feature into account. Moreover, an improved simulated annealing with variable neighborhoods structure is introduced to improve the local searching ability for the proposed algorithm. Finally, experimental results are given to show the effectiveness of the proposed algorithm.
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