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Article: Multiobjective optimisation design for enterprise system operation in the case of scheduling problem with deteriorating jobs

TitleMultiobjective optimisation design for enterprise system operation in the case of scheduling problem with deteriorating jobs
Authors
Issue Date2016
PublisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/17517575.asp
Citation
Enterprise Information Systems, 2016, v. 10 n. 3, p. 268-285 How to Cite?
AbstractThe operation process design is one of the key issues in the manufacturing and service sectors. As a typical operation process, the scheduling with consideration of the deteriorating effect has been widely studied; however, the current literature only studied single function requirement and rarely considered the multiple function requirements which are critical for a real-world scheduling process. In this article, two function requirements are involved in the design of a scheduling process with consideration of the deteriorating effect and then formulated into two objectives of a mathematical programming model. A novel multiobjective evolutionary algorithm is proposed to solve this model with combination of three strategies, i.e. a multiple population scheme, a rule-based local search method and an elitist preserve strategy. To validate the proposed model and algorithm, a series of randomly-generated instances are tested and the experimental results indicate that the model is effective and the proposed algorithm can achieve the satisfactory performance which outperforms the other state-of-the-art multiobjective evolutionary algorithms, such as nondominated sorting genetic algorithm II and multiobjective evolutionary algorithm based on decomposition, on all the test instances. © 2015 Taylor & Francis.
Persistent Identifierhttp://hdl.handle.net/10722/220153
ISSN
2015 Impact Factor: 2.269
2015 SCImago Journal Rankings: 1.287
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorWang, H-
dc.contributor.authorFu, Y-
dc.contributor.authorHuang, M-
dc.contributor.authorWang, J-
dc.date.accessioned2015-10-16T06:30:56Z-
dc.date.available2015-10-16T06:30:56Z-
dc.date.issued2016-
dc.identifier.citationEnterprise Information Systems, 2016, v. 10 n. 3, p. 268-285-
dc.identifier.issn1751-7575-
dc.identifier.urihttp://hdl.handle.net/10722/220153-
dc.description.abstractThe operation process design is one of the key issues in the manufacturing and service sectors. As a typical operation process, the scheduling with consideration of the deteriorating effect has been widely studied; however, the current literature only studied single function requirement and rarely considered the multiple function requirements which are critical for a real-world scheduling process. In this article, two function requirements are involved in the design of a scheduling process with consideration of the deteriorating effect and then formulated into two objectives of a mathematical programming model. A novel multiobjective evolutionary algorithm is proposed to solve this model with combination of three strategies, i.e. a multiple population scheme, a rule-based local search method and an elitist preserve strategy. To validate the proposed model and algorithm, a series of randomly-generated instances are tested and the experimental results indicate that the model is effective and the proposed algorithm can achieve the satisfactory performance which outperforms the other state-of-the-art multiobjective evolutionary algorithms, such as nondominated sorting genetic algorithm II and multiobjective evolutionary algorithm based on decomposition, on all the test instances. © 2015 Taylor & Francis.-
dc.languageeng-
dc.publisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/17517575.asp-
dc.relation.ispartofEnterprise Information Systems-
dc.titleMultiobjective optimisation design for enterprise system operation in the case of scheduling problem with deteriorating jobs-
dc.typeArticle-
dc.identifier.emailWang, H: wanghf@hku.hk-
dc.identifier.emailWang, J: jwwang@hku.hk-
dc.identifier.authorityWang, J=rp01888-
dc.identifier.doi10.1080/17517575.2015.1078913-
dc.identifier.scopuseid_2-s2.0-84953367902-
dc.identifier.hkuros255728-
dc.identifier.hkuros259070-
dc.identifier.volume10-
dc.identifier.issue3-
dc.identifier.spage268-
dc.identifier.epage285-
dc.identifier.isiWOS:000367809300003-
dc.publisher.placeUnited Kingdom-

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