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dc.contributor.authorTan, Yaqingen
dc.contributor.authorHuang, Weien
dc.contributor.authorSun, Yanmingen
dc.contributor.authorYue, Yongen
dc.date.accessioned2014-10-30T10:47:43Z
dc.date.available2014-10-30T10:47:43Z
dc.date.issued2014-06
dc.identifier.citationTan Y., Huang W., Sun Y., Yue Y. (2014) 'Scheduling and optimisation of batch plants: model development and comparison of approaches' International Journal of Computer Applications in Technology 49 (3/4):227en
dc.identifier.issn0952-8091
dc.identifier.issn1741-5047
dc.identifier.doi10.1504/IJCAT.2014.062359
dc.identifier.urihttp://hdl.handle.net/10547/333414
dc.description.abstractThe application of parallel machines and storage facilities provides flexibility but raises challenges for batch plants. This research proposes a scheduling model in batch plants, considering complex real-world constraints that were seldom addressed together. Two optimisation approaches, genetic algorithm (GA) and constraint programming (CP), are applied to solve the complex batch plant scheduling problem. A case study and scalability tests are conducted to investigate different performance of GA and CP in the problem to prepare for further research application. It is found that the CP approach has a better performance in solving batch plant scheduling problems with complex constraints although it needs longer time. The ‘restart’ search strategy is better than two other search strategies for the CP approach.
dc.language.isoenen
dc.publisherInderscience Publishersen
dc.relation.urlhttp://www.inderscience.com/link.php?id=62359en
dc.rightsArchived with thanks to International Journal of Computer Applications in Technologyen
dc.subjectparallel machinesen
dc.subjectbatch plantsen
dc.subjectgenetic algorithmen
dc.subjectconstraint programmingen
dc.subjectbatch plant schedulingen
dc.titleScheduling and optimisation of batch plants: model development and comparison of approachesen
dc.typeArticleen
dc.contributor.departmentUniversity of Bedfordshireen
dc.identifier.journalInternational Journal of Computer Applications in Technologyen
html.description.abstractThe application of parallel machines and storage facilities provides flexibility but raises challenges for batch plants. This research proposes a scheduling model in batch plants, considering complex real-world constraints that were seldom addressed together. Two optimisation approaches, genetic algorithm (GA) and constraint programming (CP), are applied to solve the complex batch plant scheduling problem. A case study and scalability tests are conducted to investigate different performance of GA and CP in the problem to prepare for further research application. It is found that the CP approach has a better performance in solving batch plant scheduling problems with complex constraints although it needs longer time. The ‘restart’ search strategy is better than two other search strategies for the CP approach.


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