A discrete learning fruit fly algorithm based on knowledge for the distributed no-wait flow shop scheduling with due windows

doi:10.1016/j.eswa.2022.116921

IR > 计算机与通信学院

	A discrete learning fruit fly algorithm based on knowledge for the distributed no-wait flow shop scheduling with due windows
	Zhu, Ningning1 ; Zhao, Fuqing1 ; Wang, Ling 2; Ding, Ruiqing 1; Xu, Tianpeng1 ; Jonrinaldi 3
	2022-07-15
发表期刊	Expert Systems with Applications
ISSN	0957-4174
卷号	198
摘要	The distributed no-wait flow shop scheduling problem with due windows (DNWFSPDW) is a novel and considerable model for modern production chain and large manufacturing industry. The object of total weighted earliness and tardiness (TWETdw) is a common cost indicator in application. A discrete knowledge-guided learning fruit fly optimization algorithm (DKLFOA) is proposed in this study to minimize TWET in DNWFSPDW. A knowledge-based structural initialization method (KNEHdw) is proposed to construct an effective initial solution. In the KNEHdw, the property that the job has no waiting time between processing machines in the no-wait flow shop scheduling problem is abstracted as knowledge to instruct jobs to be placed in possible positions. The swarm center expands from a single individual to an elitist swarm in the vision search stage. A probability knowledge model is established based on the sequence relationship of jobs in the elite population. The feedback information in the iterative process using the probabilistic knowledge model leads the population to search in the direction with a high success rate. The inferior individuals are allocated to the corresponding elite individuals for the local search in the olfactory search stage. The knowledge of weight in due windows is utilized to avoid invalid search during the iteration process. The variable neighborhood descent (VND) strategy is adopted in the local search to enhance the accuracy of the proposed algorithm and jump out of the local optimal. The design of experimental method (DOE) is introduced to calibrate the parameters in the algorithm. The simulation results show that DKLFOA has advantages for solving DNWFSPDW problems comparing with the state-of-the-art algorithms. © 2022 Elsevier Ltd
关键词	Fruits Iterative methods Job shop scheduling Learning algorithms Local search (optimization) Machine shop practice Manufacture Distributed no-wait flow-shop Due-window Fruit fly optimization Fruitflies Knowledge model No-wait flowshop Optimisations Probability knowledge model Variable neighborhood descend Variable neighbourhoods
DOI	10.1016/j.eswa.2022.116921
收录类别	EI ; SCIE
语种	英语
WOS研究方向	Computer Science ; Engineering ; Operations Research & Management Science
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Operations Research & Management Science
WOS记录号	WOS:000792918500008
出版者	Elsevier Ltd
EI入藏号	20221311844582
EI主题词	Knowledge based systems
EI分类号	537.1 Heat Treatment Processes ; 604.2 Machining Operations ; 723.4.1 Expert Systems ; 723.4.2 Machine Learning ; 821.4 Agricultural Products ; 913.4 Manufacturing ; 921.5 Optimization Techniques ; 921.6 Numerical Methods
来源库	WOS
引用统计	被引频次：10[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/157896
专题	计算机与通信学院科学技术处（军民融合领导小组办公室）国际合作处（港澳台办）
通讯作者	Zhao, Fuqing
作者单位	1.Lanzhou Univ Technol, Sch Comp & Commun Technol, Lanzhou 730050, Peoples R China; 2.Tsinghua Univ, Dept Automat, Beijing 10084, Peoples R China; 3.Univ Andalas, Dept Ind Engn, Padang 25163, Indonesia
第一作者单位	兰州理工大学
通讯作者单位	兰州理工大学
第一作者的第一单位	兰州理工大学
推荐引用方式 GB/T 7714	Zhu, Ningning,Zhao, Fuqing,Wang, Ling,et al. A discrete learning fruit fly algorithm based on knowledge for the distributed no-wait flow shop scheduling with due windows[J]. Expert Systems with Applications,2022,198.
APA	Zhu, Ningning,Zhao, Fuqing,Wang, Ling,Ding, Ruiqing,Xu, Tianpeng,&Jonrinaldi.(2022).A discrete learning fruit fly algorithm based on knowledge for the distributed no-wait flow shop scheduling with due windows.Expert Systems with Applications,198.
MLA	Zhu, Ningning,et al."A discrete learning fruit fly algorithm based on knowledge for the distributed no-wait flow shop scheduling with due windows".Expert Systems with Applications 198(2022).