Computationally efficient neuro-dynamic programming approximation method for the capacitated re-entrant line scheduling problem
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Choi, Jin Young | - |
dc.contributor.author | Kim, Seoung Bum | - |
dc.date.accessioned | 2021-09-07T00:06:11Z | - |
dc.date.available | 2021-09-07T00:06:11Z | - |
dc.date.created | 2021-06-18 | - |
dc.date.issued | 2012 | - |
dc.identifier.issn | 0020-7543 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/109387 | - |
dc.description.abstract | This paper presents a computationally efficient neuro-dynamic programming approximation method for the capacitated re-entrant line scheduling problem by reducing the number of feature functions. The method is based on a statistical assessment of the significance of the various feature functions. This assessment can be made by combining the weighted principal components with a thresholding algorithm. The efficacy of the new feature functions selected is tested by numerical experiments. The results indicate that the feature selection method presented here can extract a small number of significant features with the potential capability of providing a compact representation of the target value function in a neuro-dynamic programming framework. Moreover, the linear parametric architecture considered holds considerable promise as a way to provide effective and computationally efficient approximations for an optimal scheduling policy that consistently outperforms the heuristics typically employed. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | TAYLOR & FRANCIS LTD | - |
dc.subject | SEMICONDUCTOR MANUFACTURING PLANTS | - |
dc.subject | POLICIES | - |
dc.subject | SYSTEMS | - |
dc.title | Computationally efficient neuro-dynamic programming approximation method for the capacitated re-entrant line scheduling problem | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Seoung Bum | - |
dc.identifier.doi | 10.1080/00207543.2011.578596 | - |
dc.identifier.scopusid | 2-s2.0-84861381695 | - |
dc.identifier.wosid | 000304343200018 | - |
dc.identifier.bibliographicCitation | INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, v.50, no.8, pp.2353 - 2362 | - |
dc.relation.isPartOf | INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH | - |
dc.citation.title | INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH | - |
dc.citation.volume | 50 | - |
dc.citation.number | 8 | - |
dc.citation.startPage | 2353 | - |
dc.citation.endPage | 2362 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Operations Research & Management Science | - |
dc.relation.journalWebOfScienceCategory | Engineering, Industrial | - |
dc.relation.journalWebOfScienceCategory | Engineering, Manufacturing | - |
dc.relation.journalWebOfScienceCategory | Operations Research & Management Science | - |
dc.subject.keywordPlus | SEMICONDUCTOR MANUFACTURING PLANTS | - |
dc.subject.keywordPlus | POLICIES | - |
dc.subject.keywordPlus | SYSTEMS | - |
dc.subject.keywordAuthor | capacitated re-entrant line | - |
dc.subject.keywordAuthor | data mining | - |
dc.subject.keywordAuthor | feature selection | - |
dc.subject.keywordAuthor | scheduling | - |
dc.subject.keywordAuthor | neuro-dynamic programming | - |
dc.subject.keywordAuthor | principal component analysis | - |
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