NSGA-II applied to dynamic flexible job shop scheduling problems with machine breakdown

被引:17
作者
Chen, Chao [1 ]
Ji, Zhicheng [1 ]
Wang, Yan [1 ]
机构
[1] Jiangnan Univ, Minist Educ, Engn Res Ctr IoT Technol Applicat, Wuxi 214122, Peoples R China
来源
MODERN PHYSICS LETTERS B | 2018年 / 32卷 / 34-36期
基金
美国国家科学基金会;
关键词
Flexible job shop; dynamic scheduling; machine breakdown; non-dominated sorting genetic algorithm; ALGORITHM;
D O I
10.1142/S0217984918401115
中图分类号
O59 [应用物理学];
学科分类号
摘要
This paper focuses on multi-objective dynamic flexible job shop scheduling problem (MODFJSP) with machine breakdown. First, a multi-objective dynamic scheduling model is established, with objectives to minimize makespan and total machine workload. Second, according to the processing status of faulty machine, a hybrid rescheduling strategy including transfer rescheduling strategy and complete rescheduling strategy is proposed to react to stochastic machine breakdown. The performance of two rescheduling strategies is analyzed in terms of the scheduling efficiency and its stability, from the delay extent and initial scheduling deviation, respectively. Besides, the optimal adaptation conditions of both scheduling strategies are obtained. Furthermore, the non-dominated sorting genetic algorithm (NSGA-II) is employed to solve the constructed model. Experimental results demonstrate the effectiveness of the proposed strategies on reducing the impact of machine breakdown in real scheduling.
引用
收藏
页数:9
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