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Conference Paper: A Two-Level Genetic Algorithm for Scheduling in Assembly Islands with Fixed-Position Layouts

TitleA Two-Level Genetic Algorithm for Scheduling in Assembly Islands with Fixed-Position Layouts
Authors
KeywordsAssembly islands
Scheduling
Two-level GA
Issue Date2009
PublisherSpringer London.
Citation
The 16th ISPE International Conference on Concurrent Engineering, Taipei, Taiwan, 20-24 July 2009. In Global Perspective for Competitive Enterprise, Economy and Ecology, 2009, p. 17-28 How to Cite?
AbstractThis paper focuses on the scheduling problem in assembly islands environment with fixed layouts. A fixed-position assembly line is always used when products (e.g., ships and planes) are too fragile, large or heavy to move. In such configuration, products normally remain in one location for its entire manufacturing period while machines, materials and workers are moved to an assembly site called an assembly island. Such layouts can afford necessary flexibility and competitive operational efficiency for products of modest variety and production volumes. However, the high dynamics of material, equipment and manpower flows in assembly islands make the production scheduling quite difficult. The authors give the definition and mathematical model for the scheduling problem. A two-level genetic algorithm is used to obtain a near optimal solution to minimize the makespan. Experimental results show that this algorithm is more effective in airline or ship industrial manufactures than in other machine or tool final assembly companies. It also can be found that some function of the number of jobs and the number of islands is the most important factor to the time of scheduling.
Persistent Identifierhttp://hdl.handle.net/10722/100097
ISBN
ISSN

 

DC FieldValueLanguage
dc.contributor.authorQin, W-
dc.contributor.authorHuang, GQ-
dc.date.accessioned2010-09-25T18:56:39Z-
dc.date.available2010-09-25T18:56:39Z-
dc.date.issued2009-
dc.identifier.citationThe 16th ISPE International Conference on Concurrent Engineering, Taipei, Taiwan, 20-24 July 2009. In Global Perspective for Competitive Enterprise, Economy and Ecology, 2009, p. 17-28-
dc.identifier.isbn978-1-84882-761-5-
dc.identifier.issn1865-5440-
dc.identifier.urihttp://hdl.handle.net/10722/100097-
dc.description.abstractThis paper focuses on the scheduling problem in assembly islands environment with fixed layouts. A fixed-position assembly line is always used when products (e.g., ships and planes) are too fragile, large or heavy to move. In such configuration, products normally remain in one location for its entire manufacturing period while machines, materials and workers are moved to an assembly site called an assembly island. Such layouts can afford necessary flexibility and competitive operational efficiency for products of modest variety and production volumes. However, the high dynamics of material, equipment and manpower flows in assembly islands make the production scheduling quite difficult. The authors give the definition and mathematical model for the scheduling problem. A two-level genetic algorithm is used to obtain a near optimal solution to minimize the makespan. Experimental results show that this algorithm is more effective in airline or ship industrial manufactures than in other machine or tool final assembly companies. It also can be found that some function of the number of jobs and the number of islands is the most important factor to the time of scheduling.-
dc.languageeng-
dc.publisherSpringer London.-
dc.relation.ispartofGlobal Perspective for Competitive Enterprise, Economy and Ecology-
dc.subjectAssembly islands-
dc.subjectScheduling-
dc.subjectTwo-level GA-
dc.titleA Two-Level Genetic Algorithm for Scheduling in Assembly Islands with Fixed-Position Layouts-
dc.typeConference_Paper-
dc.identifier.emailQin, W: eroschin@hku.hk-
dc.identifier.emailHuang, GQ: gqhuang@hkucc.hku.hk-
dc.identifier.authorityHuang, GQ=rp00118-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/978-1-84882-762-2_2-
dc.identifier.scopuseid_2-s2.0-84866410017-
dc.identifier.hkuros160354-
dc.identifier.spage17-
dc.identifier.epage28-
dc.publisher.placeLondon, UK-
dc.identifier.issnl2365-0850-

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