A hybrid harmony search algorithm with efficient job sequence scheme and variable neighborhood search for the permutation flow shop scheduling problems

doi:10.1016/j.engappai.2017.07.023

	A hybrid harmony search algorithm with efficient job sequence scheme and variable neighborhood search for the permutation flow shop scheduling problems
	Zhao, Fuqing 1; Liu, Yang 1; Zhang, Yi 4; Ma, Weimin 2; Zhang, Chuck 3
刊名	Engineering Applications of Artificial Intelligence
	2017-10-01
卷号	65 页码:178-199
关键词	Benchmarking Combinatorial optimization Hydraulic structures Learning algorithms Machine shop practice Mapping Optimization Production control Scheduling Evolution computation Harmony search Operation research Parameter sensitivities Permutation flow-shop scheduling
ISSN号	09521976
DOI	10.1016/j.engappai.2017.07.023
英文摘要	The permutation flow shop scheduling problem (PFSSP), one of the most widely studied production scheduling problems, is a typical NP-hard combinatorial optimization problem. In this paper, a hybrid harmony search algorithm with efficient job sequence mapping scheme and variable neighborhood search (VNS), named HHS, is proposed to solve the PFFSP with the objective to minimize the makespan. First of all, to extend the HHS algorithm to solve the PFSSP effectively, an efficient smallest order value (SOV) rule based on random key is introduced to convert continuous harmony vector into a discrete job permutation after fully investigating the effect of different job sequence mapping schemes. Secondly, an effective initialization scheme, which is based on NEH heuristic mechanism combining with chaotic sequence, is employed with the aim of improving the solution's quality of the initial harmony memory (HM). Thirdly, an opposition-based learning technique in the selection process and the best harmony (best individual) in the pitch adjustment process are made full use of to accelerate convergence performances and improve solution accuracy. Meanwhile, the parameter sensitivity is studied to investigate the properties of HHS, and the recommended values of parameters adopted in HHS are presented. Finally, by making use of a novel variable neighborhood search, the efficient insert and swap structures are incorporated into the HHS to adequately emphasize local exploitation ability. Experimental simulations and comparisons on both continuous and combinatorial benchmark problems demonstrate that the HHS algorithm outperforms the standard HS algorithm and other recently proposed efficient algorithms in terms of solution quality and stability. © 2017 Elsevier Ltd
WOS研究方向	Automation & Control Systems ; Computer Science ; Engineering
语种	英语
出版者	Elsevier Ltd
WOS记录号	WOS:000413388100016
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/150185]
专题	国际合作处（港澳台办）
作者单位	1.School of Computer and Communication Technology, Lanzhou University of Technology, Lanzhou; 730050, China; 2.School of Economics and Management, Tongji University, Shanghai; 200092, China; 3.H. Milton Stewart School of Industrial & Systems Engineering, Georgia Institute of Technology, Atlanta; GA; 30332, United States 4.School of Mechanical Engineering, Xijing University, Xi'an; 710123, China;
推荐引用方式 GB/T 7714	Zhao, Fuqing,Liu, Yang,Zhang, Yi,et al. A hybrid harmony search algorithm with efficient job sequence scheme and variable neighborhood search for the permutation flow shop scheduling problems[J]. Engineering Applications of Artificial Intelligence,2017,65:178-199.
APA	Zhao, Fuqing,Liu, Yang,Zhang, Yi,Ma, Weimin,&Zhang, Chuck.(2017).A hybrid harmony search algorithm with efficient job sequence scheme and variable neighborhood search for the permutation flow shop scheduling problems.Engineering Applications of Artificial Intelligence,65,178-199.
MLA	Zhao, Fuqing,et al."A hybrid harmony search algorithm with efficient job sequence scheme and variable neighborhood search for the permutation flow shop scheduling problems".Engineering Applications of Artificial Intelligence 65(2017):178-199.