An Improved Genetic-Shuffled Frog-Leaping Algorithm for Permutation Flowshop Scheduling

doi:10.1155/2020/3450180

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室

	An Improved Genetic-Shuffled Frog-Leaping Algorithm for Permutation Flowshop Scheduling
	Wu, Peiliang 1,3,4,5; Yang, Qingyu 5; Chen, Wenbai 2; Mao, Bingyi 3,5; Yu, Hongnian 1
刊名	COMPLEXITY
	2020-11-28
卷号	2020 页码:15
ISSN号	1076-2787
DOI	10.1155/2020/3450180
通讯作者	Yu, Hongnian(yu61150@ieee.org)
英文摘要	Due to the NP-hard nature, the permutation flowshop scheduling problem (PFSSP) is a fundamental issue for Industry 4.0, especially under higher productivity, efficiency, and self-managing systems. This paper proposes an improved genetic-shuffled frog-leaping algorithm (IGSFLA) to solve the permutation flowshop scheduling problem. In the proposed IGSFLA, the optimal initial frog (individual) in the initialized group is generated according to the heuristic optimal-insert method with fitness constrain. The crossover mechanism is applied to both the subgroup and the global group to avoid the local optimal solutions and accelerate the evolution. To evolve the frogs with the same optimal fitness more outstanding, the disturbance mechanism is applied to obtain the optimal frog of the whole group at the initialization step and the optimal frog of the subgroup at the searching step. The mathematical model of PFSSP is established with the minimum production cycle (makespan) as the objective function, the fitness of frog is given, and the IGSFLA-based PFSSP is proposed. Experimental results have been given and analyzed, showing that IGSFLA not only provides the optimal scheduling performance but also converges effectively.
资助项目	National Key R&D Program of China[2018YFB1308300] ; European Commission[H2020-MSCA-RISE-2016-734875] ; China Postdoctoral Science Foundation[2018M631620] ; Natural Science Foundation of Beijing Municipality[4202026] ; Doctoral Fund of Yanshan University[BL18007]
WOS关键词	BEE COLONY ALGORITHM ; SHOP ; OPTIMIZATION
WOS研究方向	Mathematics ; Science & Technology - Other Topics
语种	英语
出版者	WILEY-HINDAWI
WOS记录号	WOS:000597936600003
资助机构	National Key R&D Program of China ; European Commission ; China Postdoctoral Science Foundation ; Natural Science Foundation of Beijing Municipality ; Doctoral Fund of Yanshan University
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/42670]
专题	自动化研究所_复杂系统管理与控制国家重点实验室
通讯作者	Yu, Hongnian
作者单位	1.Edinburgh Napier Univ, Sch Engn & Built Environm, Edinburgh EH10 5DT, Midlothian, Scotland 2.Beijing Informat Sci & Technol Univ, Sch Automat, Beijing 100101, Peoples R China 3.Key Lab Comp Virtual Technol & Syst Integrat Hebe, Qinhuangdao 066004, Hebei, Peoples R China 4.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 5.Yanshan Univ, Sch Informat Sci & Engn, Qinhuangdao 066004, Hebei, Peoples R China
推荐引用方式 GB/T 7714	Wu, Peiliang,Yang, Qingyu,Chen, Wenbai,et al. An Improved Genetic-Shuffled Frog-Leaping Algorithm for Permutation Flowshop Scheduling[J]. COMPLEXITY,2020,2020:15.
APA	Wu, Peiliang,Yang, Qingyu,Chen, Wenbai,Mao, Bingyi,&Yu, Hongnian.(2020).An Improved Genetic-Shuffled Frog-Leaping Algorithm for Permutation Flowshop Scheduling.COMPLEXITY,2020,15.
MLA	Wu, Peiliang,et al."An Improved Genetic-Shuffled Frog-Leaping Algorithm for Permutation Flowshop Scheduling".COMPLEXITY 2020(2020):15.