An improved genetic algorithm with variable neighbourhood search for flexible job-shop scheduling problem

被引:0
作者
Jia, Zerui [1 ]
Si, Chengyong [2 ]
Shen, Jianqiang [2 ]
Wang, Lei [3 ]
机构
[1] Univ Shanghai Sci & Technol, Sch Optic Elect & Comp Engn, Shanghai 200093, Peoples R China
[2] Univ Shanghai Sci & Technol, Sino German Coll, Shanghai 200093, Peoples R China
[3] Tongji Univ, Coll Elect & Informat Engn, Shanghai 201804, Peoples R China
来源
2024 43RD CHINESE CONTROL CONFERENCE, CCC 2024 | 2024年
基金
中国国家自然科学基金;
关键词
Flexible Job Shop Scheduling Problem; Genetic algorithm; Improved operator; Variable neighbourhood search; SWARM OPTIMIZATION ALGORITHM; HYBRID;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The Flexible Job Shop Scheduling Problem (FJSP), a classical NP-hard problem, requires the solution of two aspects of the complex problem, the first is to assign each operation to an available machine, and the second is to sequence each operation. In this paper, we propose an improved genetic algorithm with variable neighbourhood search(IGA-VNS), which improves the stability of the algorithm by using an improved elite pool strategy and a hybrid selection strategy, and the variable neighbourhood search algorithm (VNS), it improves the local search ability of the algorithm and makes the search process more efficient. Experiments proved the effectiveness of the algorithm.
引用
收藏
页码:2130 / 2135
页数:6
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