Please use this identifier to cite or link to this item: https://doi.org/10.1002/aic.12134
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dc.titleA novel search framework for multi-stage process scheduling with tight due dates
dc.contributor.authorHe, Y.
dc.contributor.authorHui, C.-W.
dc.date.accessioned2014-11-28T08:42:54Z
dc.date.available2014-11-28T08:42:54Z
dc.date.issued2010-08
dc.identifier.citationHe, Y., Hui, C.-W. (2010-08). A novel search framework for multi-stage process scheduling with tight due dates. AIChE Journal 56 (8) : 2103-2121. ScholarBank@NUS Repository. https://doi.org/10.1002/aic.12134
dc.identifier.issn00011541
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/112985
dc.description.abstractThis article improves the original genetic algorithm developed by He and Hui (Chem Eng Sci. 2007; 62:1504-1527) and proposes a novel global search framework (GSF) for the large-size multi-stage process scheduling problems. This work first constructs a comprehensive set of position selection rules according to the impact factors analysis presented by He and Hui (in this publication in 2007), and then selects suitable rules for schedule synthesis. In coping with infeasibility emerging during the search, a penalty function is adopted to force the algorithm to approach the feasible solutions. The large-size problems with tight due dates are challenging to the current solution techniques. Inspired by the gradient used in numerical analysis, we treat the deviation existing among the computational tests of the algorithm as evolutionary gradient. Based on this concept, a GSF is laid out to fully utilize the search ability of the current algorithm. Numerical experiments indicate that the proposed search framework solves such problems with satisfactory solutions. © 2009 American Institute of Chemical Engineers.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1002/aic.12134
dc.sourceScopus
dc.subjectEvolutionary gradient
dc.subjectGenetic algorithm
dc.subjectGlobal search framework
dc.subjectHeuristic rules
dc.subjectHybrid flow shop
dc.subjectMulti-stage process scheduling
dc.typeArticle
dc.contributor.departmentSOLAR ENERGY RESEARCH INST OF S'PORE
dc.description.doi10.1002/aic.12134
dc.description.sourcetitleAIChE Journal
dc.description.volume56
dc.description.issue8
dc.description.page2103-2121
dc.description.codenAICEA
dc.identifier.isiut000279968000014
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