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dc.contributor.authorTan, Yaqingen_GB
dc.contributor.authorHuang, Weien_GB
dc.contributor.authorSun, Yanmingen_GB
dc.contributor.authorYue, Yongen_GB
dc.date.accessioned2013-03-25T11:50:56Z
dc.date.available2013-03-25T11:50:56Z
dc.date.issued2012
dc.identifier.citationTan, Y., Huang, W., Sun, Y. & Yue, Y. (2012) 'Comparative study of different approaches to solve batch process scheduling and optimisation problems', Automation and Computing (ICAC), 2012 18th International Conference on, Automation and Computing (ICAC), 2012 18th International Conference on,p1-6.en_GB
dc.identifier.isbn9781467317221
dc.identifier.urihttp://hdl.handle.net/10547/275817
dc.description.abstractEffective approaches are important to batch process scheduling problems, especially those with complex constraints. However, most research focus on improving optimisation techniques, and those concentrate on comparing their difference are inadequate. This study develops an optimisation model of batch process scheduling problems with complex constraints and investigates the performance of different optimisation techniques, such as Genetic Algorithm (GA) and Constraint Programming (CP). It finds that CP has a better capacity to handle batch process problems with complex constraints but it costs longer time.
dc.language.isoenen
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INCen_GB
dc.relation.urlhttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=6330519en_GB
dc.subjectbatch process schedulingen_GB
dc.subjectcomparative studyen_GB
dc.subjectGenetic Algorithmen_GB
dc.subjectConstraint Programmingen_GB
dc.titleComparative study of different approaches to solve batch process scheduling and optimisation problemsen
dc.typeConference papers, meetings and proceedingsen
dc.contributor.departmentUniversity of Bedfordshireen_GB
html.description.abstractEffective approaches are important to batch process scheduling problems, especially those with complex constraints. However, most research focus on improving optimisation techniques, and those concentrate on comparing their difference are inadequate. This study develops an optimisation model of batch process scheduling problems with complex constraints and investigates the performance of different optimisation techniques, such as Genetic Algorithm (GA) and Constraint Programming (CP). It finds that CP has a better capacity to handle batch process problems with complex constraints but it costs longer time.


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