完整後設資料紀錄
DC 欄位語言
dc.contributor.authorSha, D. Y.en_US
dc.contributor.authorLin, Hsing-Hungen_US
dc.date.accessioned2014-12-08T15:07:19Z-
dc.date.available2014-12-08T15:07:19Z-
dc.date.issued2010-03-01en_US
dc.identifier.issn0957-4174en_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.eswa.2009.06.041en_US
dc.identifier.urihttp://hdl.handle.net/11536/5767-
dc.description.abstractMost previous research into the job-shop scheduling problem has concentrated on finding a single optimal Solution (e g.. makespan), even though the actual requirement of most production systems requires multi-objective optimization file aim of this paper is to construct a particle swarm optimization (PSO) for an elaborate multi-objective job-shop scheduling problem The original PSO was used to solve continuous optimization problems. Due to the discrete solution spaces of scheduling optimization problems, the authors modified the particle position representation. particle movement, and particle velocity in this Study The modified PSO was used to solve various benchmark problems Test results demonstrated that the modified PSO performed better in search quality and efficiency than traditional evolutionary heuristics. (C) 2009 Elsevier Ltd. All rights reserved.en_US
dc.language.isoen_USen_US
dc.subjectJob-shop schedulingen_US
dc.subjectParticle swarm optimizationen_US
dc.subjectMultiple objectivesen_US
dc.titleA multi-objective PSO for job-shop scheduling problemsen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.eswa.2009.06.041en_US
dc.identifier.journalEXPERT SYSTEMS WITH APPLICATIONSen_US
dc.citation.volume37en_US
dc.citation.issue2en_US
dc.citation.spage1065en_US
dc.citation.epage1070en_US
dc.contributor.department工業工程與管理學系zh_TW
dc.contributor.departmentDepartment of Industrial Engineering and Managementen_US
dc.identifier.wosnumberWOS:000272432300020-
dc.citation.woscount26-
顯示於類別:期刊論文


文件中的檔案:

  1. 000272432300020.pdf

若為 zip 檔案,請下載檔案解壓縮後,用瀏覽器開啟資料夾中的 index.html 瀏覽全文。