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http://bura.brunel.ac.uk/handle/2438/5991
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yang, S | - |
dc.contributor.author | Wang, D | - |
dc.date.accessioned | 2011-11-21T16:11:53Z | - |
dc.date.available | 2011-11-21T16:11:53Z | - |
dc.date.issued | 1999 | - |
dc.identifier.citation | Journal of Systems Engineering, 14(2), 140 - 144, June 1999 | en_US |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/5991 | - |
dc.description.abstract | A 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.iso | Chinese | en_US |
dc.subject | Job-shop scheduling | en_US |
dc.subject | Neural network | en_US |
dc.subject | Heuristics | en_US |
dc.subject | Hybrid strategy | en_US |
dc.title | A neural network and heuristics hybrid strategy for job-shop scheduling problem | en_US |
dc.type | Article | en_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 |
Files in This Item:
File | Description | Size | Format | |
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Fulltext Chinese.pdf | 431.77 kB | Adobe PDF | View/Open |
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