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dc.contributor.authorSha, D. Y.en_US
dc.contributor.authorStorch, R. L.en_US
dc.contributor.authorLiu, C. -H.en_US
dc.date.accessioned2014-12-08T15:15:00Z-
dc.date.available2014-12-08T15:15:00Z-
dc.date.issued2007-01-01en_US
dc.identifier.issn0020-7543en_US
dc.identifier.urihttp://dx.doi.org/10.1080/00207540500507435en_US
dc.identifier.urihttp://hdl.handle.net/11536/11281-
dc.description.abstractMany regression-based methods to date have been proposed for solving the due date assignment (DDA) problem. The advantages of regression-based DDA methods are that they are easy to both put into practice and comprehend. However, relatively little scheduling research has focused on improving the performances of regression-based DDA methods. The performance of a regression-based DDA method could be improved if its values of regression coefficients could provide a more accurate and precise flowtime estimation for each individual job. The difficulty in doing this stems from the dynamic and stochastic nature of production environment that precludes accurate estimation. Therefore, the aim of this study is to suggest a particular methodology for setting the regression coefficients to improve the performance of regression-based DDA method. In particular, the regression-based DDA method achieved by our suggested methodology is able to adjust the values of coefficients dynamically to best predict the job due date based on the condition of the shop at the instant of job entry. To evaluate the robustness of the methodology, an experimental design was used with four regression coefficient determining procedures, two shop models, and three dispatching rules. The results of this investigation clearly indicate that significant improvements in the performance of regression-based DDA method can occur when the suggested methodology is used.en_US
dc.language.isoen_USen_US
dc.subjectdue date assignmenten_US
dc.subjectregression-based methoden_US
dc.subjectdynamic tuningen_US
dc.titleDevelopment of a regression-based method with case-based tuning to solve the due date assignment problemen_US
dc.typeArticleen_US
dc.identifier.doi10.1080/00207540500507435en_US
dc.identifier.journalINTERNATIONAL JOURNAL OF PRODUCTION RESEARCHen_US
dc.citation.volume45en_US
dc.citation.issue1en_US
dc.citation.spage65en_US
dc.citation.epage82en_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:000242019100004-
dc.citation.woscount10-
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