An Improved Hybrid Quantum Particle Swarm Optimization Algorithm for FJSP

doi:10.1145/3318299.3318359

	An Improved Hybrid Quantum Particle Swarm Optimization Algorithm for FJSP
	Zhang, Qiwen; Hu, Songqi
	2019
关键词	FJSP quantum particle swarm optimization (QPSO) Levy flights elitist strategy
DOI	10.1145/3318299.3318359
页码	246-252
英文摘要	Aiming at minimizing makespan (the end time of the final machine) in flexible job shop scheduling problems (FJSP), a hybrid quantum behaved particle swarm optimization algorithm based on Levy flights is proposed in this paper. Firstly, the algorithm uses the quantum probability amplitude coding method to establish a relationship between the process sequence and the particle position to solve job process sequencing sub-problem. Then uses the global selection, local selection and probability random selection to select the machine for each process. Finally, the Levy flights is used to improve variant mode and enhance the effect of variation, the elitist strategy combined with neighborhood search is used after each iteration to improve the quality of the results. Experiments in a classical case show that the algorithm is effective and feasible for solving flexible job shop scheduling problems.
会议录	ICMLC 2019: 2019 11TH INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND COMPUTING
会议录出版者	ASSOC COMPUTING MACHINERY
会议录出版地	1515 BROADWAY, NEW YORK, NY 10036-9998 USA
语种	英语
资助项目	National Natural Science Foundation of China[61862041]
WOS研究方向	Computer Science ; Engineering
WOS记录号	WOS:000477981500043
内容类型	会议论文
源URL	[http://119.78.100.223/handle/2XXMBERH/36098]
专题	计算机与通信学院
通讯作者	Zhang, Qiwen
作者单位	Lanzhou Univ Technol, Sch Comp & Commun, 287 Langongping Rd, Lanzhou 730050, Gansu, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Qiwen,Hu, Songqi. An Improved Hybrid Quantum Particle Swarm Optimization Algorithm for FJSP[C]. 见:.