File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1080/17517575.2015.1078913
- Scopus: eid_2-s2.0-84953367902
- WOS: WOS:000367809300003
- Find via
Supplementary
- Citations:
- Appears in Collections:
Article: Multiobjective optimisation design for enterprise system operation in the case of scheduling problem with deteriorating jobs
Title | Multiobjective optimisation design for enterprise system operation in the case of scheduling problem with deteriorating jobs |
---|---|
Authors | |
Keywords | deteriorating effect enterprise system multiobjective evolutionary algorithm multiobjective scheduling Operation process design |
Issue Date | 2016 |
Publisher | Taylor & 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? |
Abstract | The 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 Identifier | http://hdl.handle.net/10722/220153 |
ISSN | 2023 Impact Factor: 4.4 2023 SCImago Journal Rankings: 0.875 |
ISI Accession Number ID |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Wang, H | - |
dc.contributor.author | Fu, Y | - |
dc.contributor.author | Huang, M | - |
dc.contributor.author | Wang, J | - |
dc.date.accessioned | 2015-10-16T06:30:56Z | - |
dc.date.available | 2015-10-16T06:30:56Z | - |
dc.date.issued | 2016 | - |
dc.identifier.citation | Enterprise Information Systems, 2016, v. 10 n. 3, p. 268-285 | - |
dc.identifier.issn | 1751-7575 | - |
dc.identifier.uri | http://hdl.handle.net/10722/220153 | - |
dc.description.abstract | The 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.language | eng | - |
dc.publisher | Taylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/17517575.asp | - |
dc.relation.ispartof | Enterprise Information Systems | - |
dc.subject | deteriorating effect | - |
dc.subject | enterprise system | - |
dc.subject | multiobjective evolutionary algorithm | - |
dc.subject | multiobjective scheduling | - |
dc.subject | Operation process design | - |
dc.title | Multiobjective optimisation design for enterprise system operation in the case of scheduling problem with deteriorating jobs | - |
dc.type | Article | - |
dc.identifier.email | Wang, H: wanghf@hku.hk | - |
dc.identifier.email | Wang, J: jwwang@hku.hk | - |
dc.identifier.authority | Wang, J=rp01888 | - |
dc.identifier.doi | 10.1080/17517575.2015.1078913 | - |
dc.identifier.scopus | eid_2-s2.0-84953367902 | - |
dc.identifier.hkuros | 255728 | - |
dc.identifier.hkuros | 259070 | - |
dc.identifier.volume | 10 | - |
dc.identifier.issue | 3 | - |
dc.identifier.spage | 268 | - |
dc.identifier.epage | 285 | - |
dc.identifier.isi | WOS:000367809300003 | - |
dc.publisher.place | United Kingdom | - |
dc.identifier.issnl | 1751-7575 | - |