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Article: Production scheduling and cell formation for virtual cellular manufacturing systems

TitleProduction scheduling and cell formation for virtual cellular manufacturing systems
Authors
KeywordsCell formation problem
Genetic algorithms
Production scheduling
Virtual cellular manufacturing system
Issue Date2002
PublisherSpringer U K. The Journal's web site is located at http://www.springer.com/engineering/production+eng/journal/170
Citation
International Journal Of Advanced Manufacturing Technology, 2002, v. 20 n. 2, p. 144-152 How to Cite?
AbstractIn this paper, an approach using the concept of genetic algorithms is proposed as a powerful but simple means of scheduling the manufacturing operations of a virtual cellular manufacturing system (VCMS). A mathematical model is developed to describe the characteristics of a VCMs, which includes the constraints related to the delivery due dates of the various products and the maximum capacities of the manufacturing resources. The objectives are to set up virtual manufacturing cells and to formulate feasible production schedules for all manufacturing operations, in order to minimise the total material and component travelling distance incurred in manufacturing the products. A new genetic based scheduling algorithm is proposed as an optimisation tool to determine the solution. The proposed algorithm differs from the conventional genetic algorithms in that the populations of the candidate solutions consist of individuals from various age-groups, and each individual is incorporated with an age attribute to enable its birth and survival rates to be governed by predefined ageing patterns. By generating the evolution of the populations with the genetic operators of selection, crossover and mutation, the proposed approach provides excellent results by maintaining a better balance between the exploitation and the exploration of the solution space, and thus improves the computational speed and the solution quality. The condition ensuring stable search performance is also derived. The superiority of the proposed algorithm is illustrated by solving the production-scheduling and cell-formation problems for a virtual cellular manufacturing system, and the results are compared with those obtained by using a conventional optimisation technique.
Persistent Identifierhttp://hdl.handle.net/10722/74346
ISSN
2015 Impact Factor: 1.568
2015 SCImago Journal Rankings: 0.915
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorMak, KLen_HK
dc.contributor.authorWang, XXen_HK
dc.date.accessioned2010-09-06T07:00:26Z-
dc.date.available2010-09-06T07:00:26Z-
dc.date.issued2002en_HK
dc.identifier.citationInternational Journal Of Advanced Manufacturing Technology, 2002, v. 20 n. 2, p. 144-152en_HK
dc.identifier.issn0268-3768en_HK
dc.identifier.urihttp://hdl.handle.net/10722/74346-
dc.description.abstractIn this paper, an approach using the concept of genetic algorithms is proposed as a powerful but simple means of scheduling the manufacturing operations of a virtual cellular manufacturing system (VCMS). A mathematical model is developed to describe the characteristics of a VCMs, which includes the constraints related to the delivery due dates of the various products and the maximum capacities of the manufacturing resources. The objectives are to set up virtual manufacturing cells and to formulate feasible production schedules for all manufacturing operations, in order to minimise the total material and component travelling distance incurred in manufacturing the products. A new genetic based scheduling algorithm is proposed as an optimisation tool to determine the solution. The proposed algorithm differs from the conventional genetic algorithms in that the populations of the candidate solutions consist of individuals from various age-groups, and each individual is incorporated with an age attribute to enable its birth and survival rates to be governed by predefined ageing patterns. By generating the evolution of the populations with the genetic operators of selection, crossover and mutation, the proposed approach provides excellent results by maintaining a better balance between the exploitation and the exploration of the solution space, and thus improves the computational speed and the solution quality. The condition ensuring stable search performance is also derived. The superiority of the proposed algorithm is illustrated by solving the production-scheduling and cell-formation problems for a virtual cellular manufacturing system, and the results are compared with those obtained by using a conventional optimisation technique.en_HK
dc.languageengen_HK
dc.publisherSpringer U K. The Journal's web site is located at http://www.springer.com/engineering/production+eng/journal/170en_HK
dc.relation.ispartofInternational Journal of Advanced Manufacturing Technologyen_HK
dc.subjectCell formation problemen_HK
dc.subjectGenetic algorithmsen_HK
dc.subjectProduction schedulingen_HK
dc.subjectVirtual cellular manufacturing systemen_HK
dc.titleProduction scheduling and cell formation for virtual cellular manufacturing systemsen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0268-3768&volume=20&spage=144&epage=152&date=2002&atitle=Production+scheduling+and+cell+formation+for+virtual+cellular+manufacturing+systemsen_HK
dc.identifier.emailMak, KL:makkl@hkucc.hku.hken_HK
dc.identifier.authorityMak, KL=rp00154en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/s001700200136en_HK
dc.identifier.scopuseid_2-s2.0-0036354947en_HK
dc.identifier.hkuros71946en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0036354947&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume20en_HK
dc.identifier.issue2en_HK
dc.identifier.spage144en_HK
dc.identifier.epage152en_HK
dc.identifier.isiWOS:000177634900009-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridMak, KL=7102680226en_HK
dc.identifier.scopusauthoridWang, XX=9246057600en_HK

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