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Conference Paper: A two-stage approach based on ant colony optimization algorithm for integrated process planning and scheduling

TitleA two-stage approach based on ant colony optimization algorithm for integrated process planning and scheduling
Authors
Zhang, SWong, TNZhang, LWan, SY
KeywordsAnt Colony Optimization
Integrated Process Planning and Scheduling
Two-stage ACO
Issue Date2011
PublisherCIE41.
Citation
The 41st International Conference on Computer and Industrial Engineering (CIE41), Los Angeles, CA.,23-25 October 2011. In Proceedings of CIE41, 2011, p. 804-809, no. 266 How to Cite?
AbstractThis paper presents a two-stage heuristic using Ant Colony Optimization (ACO) to solve Integrated Process Planning and scheduling (IPPS) problem. The algorithm is incorporated with the objective of obtaining an optimal or near optimal schedule for a number of jobs with multi-operations. A graphical search method is used, where artificial ants are assigned as software agents to search for routines corresponding to schedules. A new approach is attempted in this paper in which the ACO solution process has been separated into two stages. Criteria including makespan and CPU time are used as measurements of performance. Illustrative examples are given to make comparisons with former research.
Persistent Identifierhttp://hdl.handle.net/10722/143927
ISSN
2164-8689
2020 SCImago Journal Rankings: 0.123

 

DC FieldValueLanguage
dc.contributor.authorZhang, Sen_US
dc.contributor.authorWong, TNen_US
dc.contributor.authorZhang, Len_US
dc.contributor.authorWan, SYen_US
dc.date.accessioned2011-12-21T08:58:43Z-
dc.date.available2011-12-21T08:58:43Z-
dc.date.issued2011en_US
dc.identifier.citationThe 41st International Conference on Computer and Industrial Engineering (CIE41), Los Angeles, CA.,23-25 October 2011. In Proceedings of CIE41, 2011, p. 804-809, no. 266en_US
dc.identifier.issn2164-8689-
dc.identifier.urihttp://hdl.handle.net/10722/143927-
dc.description.abstractThis paper presents a two-stage heuristic using Ant Colony Optimization (ACO) to solve Integrated Process Planning and scheduling (IPPS) problem. The algorithm is incorporated with the objective of obtaining an optimal or near optimal schedule for a number of jobs with multi-operations. A graphical search method is used, where artificial ants are assigned as software agents to search for routines corresponding to schedules. A new approach is attempted in this paper in which the ACO solution process has been separated into two stages. Criteria including makespan and CPU time are used as measurements of performance. Illustrative examples are given to make comparisons with former research.-
dc.languageengen_US
dc.publisherCIE41.-
dc.relation.ispartofProceedings of the 41st International Conference on Computer and Industrial Engineering, CIE41en_US
dc.subjectAnt Colony Optimization-
dc.subjectIntegrated Process Planning and Scheduling-
dc.subjectTwo-stage ACO-
dc.titleA two-stage approach based on ant colony optimization algorithm for integrated process planning and schedulingen_US
dc.typeConference_Paperen_US
dc.identifier.emailZhang, S: h1095072@hku.hken_US
dc.identifier.emailWong, TN: tnwong@hku.hk-
dc.identifier.emailZhang, L: nguzlp@hku.hk-
dc.identifier.emailWan, SY: wanszeyuen@msn.com-
dc.identifier.authorityWong, TN=rp00192en_US
dc.description.naturelink_to_OA_fulltext-
dc.identifier.hkuros197930en_US
dc.identifier.spage804en_US
dc.identifier.epage809, no. 266en_US
dc.publisher.placeUnited States-
dc.description.otherThe 41st International Conference on Computer and Industrial Engineering (CIE41), Los Angeles, CA.,23-25 October 2011. In Proceedings of CIE41, 2011, p. 804-809, no. 266-
dc.identifier.issnl2164-8670-

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