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Article: An ant colony optimization algorithm for scheduling virtual cellular manufacturing systems

TitleAn ant colony optimization algorithm for scheduling virtual cellular manufacturing systems
Authors
KeywordsAnt colony optimization
Manufacturing cell creation
Production scheduling
Virtual cellular manufacturing cells
Issue Date2007
PublisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/0951192X.asp
Citation
International Journal Of Computer Integrated Manufacturing, 2007, v. 20 n. 6, p. 524-537 How to Cite?
AbstractThis paper presents a methodology to solve the manufacturing cell creation and the production scheduling problems for designing virtual cellular manufacturing systems (VCMSs). The objective is to minimize the total materials and components travelling distance incurred. The methodology consists of (i) a mathematical model that describes the characteristics of a VCMS and includes constraints such as delivery due dates of products, maximum capacities of resources, critical tools limitation, and (ii) an ant colony optimization (ACO) algorithm for manufacturing cell formation and production scheduling. Since the proposed ACO algorithm does not indicate a feasible schedule explicitly, two simple heuristics are developed to assign workstations to the operations of the jobs, and to construct the final schedule. To demonstrate the effectiveness of the proposed methodology, both the ACO algorithm and the genetic algorithm are applied to design manufacturing cells for a company in China producing internal combustion engine components. Comparison of the results obtained with the results supplied by the company on the existing manufacturing system show that both the ACO algorithm and the genetic algorithm together with the virtual cellular manufacturing concept perform better than the current manufacturing practice in terms of average workstation utilization, product completion time and system throughput. Also, the results of a set of randomly generated numerical experiments show that the proposed ACO algorithm generates excellent final solutions in a much shorter computation time when compared with the genetic algorithm. Therefore, the mathematical model and the ACO algorithm proposed in this paper form a simple, but effective and efficient methodology to solve the manufacturing cell creation and production scheduling problems for designing VCMSs.
Persistent Identifierhttp://hdl.handle.net/10722/74453
ISSN
2015 Impact Factor: 1.319
2015 SCImago Journal Rankings: 0.673
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorMak, KLen_HK
dc.contributor.authorPeng, Pen_HK
dc.contributor.authorWang, XXen_HK
dc.contributor.authorLau, TLen_HK
dc.date.accessioned2010-09-06T07:01:29Z-
dc.date.available2010-09-06T07:01:29Z-
dc.date.issued2007en_HK
dc.identifier.citationInternational Journal Of Computer Integrated Manufacturing, 2007, v. 20 n. 6, p. 524-537en_HK
dc.identifier.issn0951-192Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/74453-
dc.description.abstractThis paper presents a methodology to solve the manufacturing cell creation and the production scheduling problems for designing virtual cellular manufacturing systems (VCMSs). The objective is to minimize the total materials and components travelling distance incurred. The methodology consists of (i) a mathematical model that describes the characteristics of a VCMS and includes constraints such as delivery due dates of products, maximum capacities of resources, critical tools limitation, and (ii) an ant colony optimization (ACO) algorithm for manufacturing cell formation and production scheduling. Since the proposed ACO algorithm does not indicate a feasible schedule explicitly, two simple heuristics are developed to assign workstations to the operations of the jobs, and to construct the final schedule. To demonstrate the effectiveness of the proposed methodology, both the ACO algorithm and the genetic algorithm are applied to design manufacturing cells for a company in China producing internal combustion engine components. Comparison of the results obtained with the results supplied by the company on the existing manufacturing system show that both the ACO algorithm and the genetic algorithm together with the virtual cellular manufacturing concept perform better than the current manufacturing practice in terms of average workstation utilization, product completion time and system throughput. Also, the results of a set of randomly generated numerical experiments show that the proposed ACO algorithm generates excellent final solutions in a much shorter computation time when compared with the genetic algorithm. Therefore, the mathematical model and the ACO algorithm proposed in this paper form a simple, but effective and efficient methodology to solve the manufacturing cell creation and production scheduling problems for designing VCMSs.en_HK
dc.languageengen_HK
dc.publisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/0951192X.aspen_HK
dc.relation.ispartofInternational Journal of Computer Integrated Manufacturingen_HK
dc.subjectAnt colony optimizationen_HK
dc.subjectManufacturing cell creationen_HK
dc.subjectProduction schedulingen_HK
dc.subjectVirtual cellular manufacturing cellsen_HK
dc.titleAn ant colony optimization algorithm for scheduling virtual cellular manufacturing systemsen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0951-192X&volume=20&issue=6&spage=524&epage=537&date=2007&atitle=An+Ant+Colony+Optimization+Algorithm+For+Scheduling+Virtual+Cellular+Manufacturing+Systemsen_HK
dc.identifier.emailMak, KL:makkl@hkucc.hku.hken_HK
dc.identifier.emailLau, TL:tllau@hkucc.hku.hken_HK
dc.identifier.authorityMak, KL=rp00154en_HK
dc.identifier.authorityLau, TL=rp00138en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1080/09511920600596821en_HK
dc.identifier.scopuseid_2-s2.0-34547515967en_HK
dc.identifier.hkuros153736en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-34547515967&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume20en_HK
dc.identifier.issue6en_HK
dc.identifier.spage524en_HK
dc.identifier.epage537en_HK
dc.identifier.isiWOS:000248334000002-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridMak, KL=7102680226en_HK
dc.identifier.scopusauthoridPeng, P=7102844225en_HK
dc.identifier.scopusauthoridWang, XX=9246057600en_HK
dc.identifier.scopusauthoridLau, TL=7102222436en_HK

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