Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/5991
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dc.contributor.authorYang, S-
dc.contributor.authorWang, D-
dc.date.accessioned2011-11-21T16:11:53Z-
dc.date.available2011-11-21T16:11:53Z-
dc.date.issued1999-
dc.identifier.citationJournal of Systems Engineering, 14(2), 140 - 144, June 1999en_US
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/5991-
dc.description.abstractA new efficient neural network and heuristics hybrid strategy for job-shop scheduling is presented. The neural network has the property of adapting its connection weights and biases of neural units while solving feasible solution. Heuristics are used to accelerate the solving process of neural network and guarantee its convergence, and to obtain non-schedule schedule from solved feasible solution by neural network with orders of operations determined and unchanged. Computer simulations have shown that the proposed hybrid strategy is of high speed and excellent efficiency.en_US
dc.language.isoChineseen_US
dc.subjectJob-shop schedulingen_US
dc.subjectNeural networken_US
dc.subjectHeuristicsen_US
dc.subjectHybrid strategyen_US
dc.titleA neural network and heuristics hybrid strategy for job-shop scheduling problemen_US
dc.typeArticleen_US
pubs.organisational-data/Brunel-
pubs.organisational-data/Brunel/Brunel (Active)-
pubs.organisational-data/Brunel/Brunel (Active)/School of Info. Systems, Comp & Maths-
pubs.organisational-data/Brunel/Research Centres (RG)-
pubs.organisational-data/Brunel/Research Centres (RG)/CIKM-
pubs.organisational-data/Brunel/School of Information Systems, Computing and Mathematics (RG)-
pubs.organisational-data/Brunel/School of Information Systems, Computing and Mathematics (RG)/CIKM-
Appears in Collections:Computer Science
Dept of Computer Science Research Papers

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