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dc.contributor.authorLenin, N.
dc.contributor.authorSiva Kumar, M.
dc.contributor.authorIslam, Mohammad Nazrul
dc.date.accessioned2017-01-30T10:26:02Z
dc.date.available2017-01-30T10:26:02Z
dc.date.created2012-12-11T20:00:28Z
dc.date.issued2012
dc.identifier.citationLenin, N. and Siva Kumar, M. and Islam, M.N. and Ravindran, D. 2012. Multi-objective optimization in single-row layout design using a genetic algorithm. International Journal of Advanced Manufacturing Technology. 67 (5): pp. 1777-1790.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/2776
dc.description.abstract

This paper presents the development of a genetic algorithm for determining a common linear machine sequence for multi-products with different operation sequences and facilities with a limited number of duplicate machine types available for a job. This work aims to minimize the total flow distance travelled by products, reduce the number of machines arranged in the final linear sequence, and decrease the total investment cost of the machines used in the final sequence. We assume that product flow runs only in the forward direction, either via in-sequence or bypass movement. We demonstrate the effectiveness of the proposed algorithm by solving a typical layout design problem taken from literature, and several randomly generated problems. Results indicate that the proposed algorithm serves as a practical decision support tool for resolving layout problems in manufacturing facilities.

dc.publisherSpringer U K
dc.subjectFacility layout
dc.subjectGenetic algorithm
dc.subjectMachine investment
dc.subjectLinear sequencing
dc.subjectFlow distance
dc.titleMulti-objective optimization in single-row layout design using a genetic algorithm
dc.typeJournal Article
dcterms.source.volume1
dcterms.source.startPage1
dcterms.source.endPage14
dcterms.source.issn0268-3768
dcterms.source.titleInternational Journal of Advanced Manufacturing Technology
curtin.note

The final publication is available at http://www.springerlink.com

curtin.department
curtin.accessStatusOpen access


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