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Swarm intelligent algorithm for re-entrant hybrid flow shop scheduling problems
Han ZH(韩忠华)1,2; Tian, Xutian1; Dong XT(董晓婷)3; Xie, Fanyi1
Department数字工厂研究室
Source PublicationInternational Journal of Simulation and Process Modelling
ISSN1740-2123
2019
Volume14Issue:1Pages:17-27
Indexed ByEI
EI Accession number20190706496876
Contribution Rank1
Funding OrganizationLiaoning Provincial Science Foundation(No. 201602608) ; Project of Liaoning Province Education Department(No. LJZ2017015) ; Shenyang Municipal Science and Technology Project (No. Z18-5-015) ; Project of Sichuan Province Education Department (No. 17ZB0823).
Keywordre-entrant hybrid flow shop RHFS mathematics scheduling models Hamming distance Levy flight swarm intelligent algorithm
AbstractIn order to solve re-entrant hybrid flowshop (RHFS) scheduling problems and establish simulations and processing models, this paper uses wolf pack algorithm (WPA) as global optimisation. For local assignment, it takes minimum remaining time rule. Scouting behaviours of wolf are changed in former optimisation by means of Levy flight, extending searching ranges and increasing rapidity of convergence. When it comes to local extremum of WPA, dynamic regenerating individuals with high similarity adds diversity. Hamming distance is used to judge individual similarity for increased quality of individuals, enhanced search performance of the algorithm in solution space and promoted evolutionary vitality. A painting workshop in a bus manufacture enterprise owns typical features of re-entrant hybrid flowshop. Regarding it as the algorithm applied target, this paper focuses on resolving this problem with dynamic wolf pack algorithm based on levy flight (LDWPA). Results show that LDWPA can solve re-entrant hybrid flowshop scheduling problems effectively.
Language英语
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/24159
Collection数字工厂研究室
Corresponding AuthorTian, Xutian
Affiliation1.Faculty of Information and Control Engineering, Shenyang Jianzhu University, Shenyang, Liaoning, China
2.Department of Digital Factory, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, Liaoning, China
3.Faculty of Electrical Engineering, Sichuan College of Architectural Technology, Deyang, Sichuan, China
Recommended Citation
GB/T 7714
Han ZH,Tian, Xutian,Dong XT,et al. Swarm intelligent algorithm for re-entrant hybrid flow shop scheduling problems[J]. International Journal of Simulation and Process Modelling,2019,14(1):17-27.
APA Han ZH,Tian, Xutian,Dong XT,&Xie, Fanyi.(2019).Swarm intelligent algorithm for re-entrant hybrid flow shop scheduling problems.International Journal of Simulation and Process Modelling,14(1),17-27.
MLA Han ZH,et al."Swarm intelligent algorithm for re-entrant hybrid flow shop scheduling problems".International Journal of Simulation and Process Modelling 14.1(2019):17-27.
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