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Conference Paper: Integrated process planning and scheduling - Multi-agent system with two-stage ant colony optimisation algorithm

TitleIntegrated process planning and scheduling - Multi-agent system with two-stage ant colony optimisation algorithm
Authors
KeywordsAnt Colony Optimisation
Integrated Process Planning And Scheduling
Multi-Agent System
Process Planning
Scheduling
Issue Date2012
PublisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/00207543.asp
Citation
International Journal Of Production Research, 2012, v. 50 n. 21, p. 6188-6201 How to Cite?
AbstractIn this paper, a two-stage ant colony optimisation (ACO) algorithm is implemented in a multi-agent system (MAS) to accomplish integrated process planning and scheduling (IPPS) in the job shop type flexible manufacturing environments. Traditionally, process planning and scheduling functions are performed sequentially and the actual status of the production facilities is not considered in either process planning or scheduling. IPPS is to combine both the process planning and scheduling problems in the consideration, that is, the actual process plan and the schedule are determined dynamically in accordance with the order details and the status of the manufacturing system. The ACO algorithm can be applied to solve IPPS problems. An innovative two-stage ACO algorithm is introduced in this paper. In the first stage of the algorithm, instead of depositing pheromones on graph edges as in common ant algorithms, ants are directed to deposit pheromones at the nodes to select a set of more favourable processes. In the second stage, the set of nodes not selected in the first stage will be ignored, and pheromones will be deposited along the graph edges while the ants traverse the paths connecting the selected set of nodes. © 2012 Copyright Taylor and Francis Group, LLC.
Persistent Identifierhttp://hdl.handle.net/10722/178253
ISSN
2015 Impact Factor: 1.693
2015 SCImago Journal Rankings: 1.445
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorWong, TNen_US
dc.contributor.authorZhang, Sen_US
dc.contributor.authorWang, Gen_US
dc.contributor.authorZhang, Len_US
dc.date.accessioned2012-12-19T09:44:24Z-
dc.date.available2012-12-19T09:44:24Z-
dc.date.issued2012en_US
dc.identifier.citationInternational Journal Of Production Research, 2012, v. 50 n. 21, p. 6188-6201en_US
dc.identifier.issn0020-7543en_US
dc.identifier.urihttp://hdl.handle.net/10722/178253-
dc.description.abstractIn this paper, a two-stage ant colony optimisation (ACO) algorithm is implemented in a multi-agent system (MAS) to accomplish integrated process planning and scheduling (IPPS) in the job shop type flexible manufacturing environments. Traditionally, process planning and scheduling functions are performed sequentially and the actual status of the production facilities is not considered in either process planning or scheduling. IPPS is to combine both the process planning and scheduling problems in the consideration, that is, the actual process plan and the schedule are determined dynamically in accordance with the order details and the status of the manufacturing system. The ACO algorithm can be applied to solve IPPS problems. An innovative two-stage ACO algorithm is introduced in this paper. In the first stage of the algorithm, instead of depositing pheromones on graph edges as in common ant algorithms, ants are directed to deposit pheromones at the nodes to select a set of more favourable processes. In the second stage, the set of nodes not selected in the first stage will be ignored, and pheromones will be deposited along the graph edges while the ants traverse the paths connecting the selected set of nodes. © 2012 Copyright Taylor and Francis Group, LLC.en_US
dc.languageengen_US
dc.publisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/00207543.aspen_US
dc.relation.ispartofInternational Journal of Production Researchen_US
dc.subjectAnt Colony Optimisationen_US
dc.subjectIntegrated Process Planning And Schedulingen_US
dc.subjectMulti-Agent Systemen_US
dc.subjectProcess Planningen_US
dc.subjectSchedulingen_US
dc.titleIntegrated process planning and scheduling - Multi-agent system with two-stage ant colony optimisation algorithmen_US
dc.typeConference_Paperen_US
dc.identifier.emailWong, TN: tnwong@hku.hken_US
dc.identifier.authorityWong, TN=rp00192en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1080/00207543.2012.720393en_US
dc.identifier.scopuseid_2-s2.0-84868217816en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-84868217816&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume50en_US
dc.identifier.issue21en_US
dc.identifier.spage6188en_US
dc.identifier.epage6201en_US
dc.identifier.isiWOS:000310597100011-
dc.publisher.placeUnited Kingdomen_US
dc.identifier.scopusauthoridWong, TN=55301015400en_US
dc.identifier.scopusauthoridZhang, S=55443734300en_US
dc.identifier.scopusauthoridWang, G=36618061900en_US
dc.identifier.scopusauthoridZhang, L=55295535400en_US

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