Scheduling of Dynamic Multi-Objective Flexible Enterprise Job-Shop Problem Based on Hybrid QPSO

被引:11
|
作者
Chen, Wei [1 ,2 ]
Yang, Hong [3 ]
Hao, Yifei [4 ]
机构
[1] Chongqing Technol & Business Univ, Res Ctr Enterprise Management, Chongqing 400067, Peoples R China
[2] Chongqing Technol & Business Univ, Sch Management, Chongqing 400067, Peoples R China
[3] Chongqing Normal Univ, Sch Geog & Tourism, Chongqing 401331, Peoples R China
[4] Chongqing Technol & Business Univ, Coll Math & Stat, Chongqing 400067, Peoples R China
来源
IEEE ACCESS | 2019年 / 7卷
关键词
Flexible job-shop scheduling; quantum particle swarm optimization; quantum gate rotation angle; double chain quantum coding; GENETIC ALGORITHM; OPTIMIZATION; TIME;
D O I
10.1109/ACCESS.2019.2938773
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In view of the importance of flexible job-shop scheduling problem (FJSP) in actual production, this paper constructs a mathematical model of fuzzy FJSP and then proposes a mixed quantum algorithm based on local optimization strategy and improved optimization rotation angle. For improving the production process, a double chain coding method was designed with two gene chains, which respectively represent the machine selection and the process sequencing. Next, the hybrid quantum particle swarm optimization (QPSO) was introduced to ensure the scheduling efficiency. Finally, the prototype system of the proposed strategy was simulated by using some actual examples. The results show that the proposed algorithm can quickly form an adjusted plan that has minimal difference from the original plan.
引用
收藏
页码:127090 / 127097
页数:8
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