A simulation-based differential evolution algorithm for stochastic parallel machine scheduling with operational considerations

We consider a parallel machine scheduling problem with the objective of minimizing two types of costs: the cost related to production operations and the cost related to due date performances. The former could be reduced by reasonable settings of the operational variables (e.g., the number of workers...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:International transactions in operational research Ročník 20; číslo 4; s. 533 - 557
Hlavní autoři: Zhang, Rui, Song, Shiji, Wu, Cheng
Médium: Journal Article
Jazyk:angličtina
Vydáno: Oxford Blackwell Publishing Ltd 01.07.2013
Pergamon
Témata:
ISSN:0969-6016, 1475-3995
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:We consider a parallel machine scheduling problem with the objective of minimizing two types of costs: the cost related to production operations and the cost related to due date performances. The former could be reduced by reasonable settings of the operational variables (e.g., the number of workers, the frequency of maintenance), while the latter could be reduced by appropriate scheduling of the production process. However, the optimization of both targets is significantly complicated by the influence of human factors that play a dominant role in real‐world manufacturing systems. To cope with this issue, a simulation‐based optimization framework is adopted in this paper for obtaining high‐quality robust solutions to the integrated scheduling problem. Meanwhile, differential evolution, a metaheuristic algorithm based on swarm intelligence, is applied for a systematic search of the huge solution space. Finally, numerical computations are conducted to verify the effectiveness of the proposed approach. Sensitivity analysis and practical implications are also presented.
Bibliografie:ArticleID:ITOR12011
National Natural Science Foundation of China - No. 61104176; No. 61273233
Social Sciences Research Project of Jiangxi Provincial Education Department - No. GL1236
ark:/67375/WNG-B91NBTHQ-4
Science and Technology Project of Jiangxi Provincial Education Department - No. GJJ12131
istex:DCDB7C6898A60C1F309074E28009B0B1EE2FC5A4
Educational Science Research Project of Jiangxi Province - No. 12YB114
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ObjectType-Article-1
ObjectType-Feature-2
content type line 23
ISSN:0969-6016
1475-3995
DOI:10.1111/itor.12011