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http://bura.brunel.ac.uk/handle/2438/5893Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Zhao, K | - |
| dc.contributor.author | Yang, S | - |
| dc.contributor.author | Wang, D | - |
| dc.date.accessioned | 2011-10-03T09:02:27Z | - |
| dc.date.available | 2011-10-03T09:02:27Z | - |
| dc.date.issued | 1998 | - |
| dc.identifier.citation | IASTED International Conference on Applied Modelling and Simulation (AMS'98), Calgary, Alberta, Canada: 110 - 114 | en_US |
| dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/5893 | - |
| dc.description | Copyright @ 1998 ACTA Press | en_US |
| dc.description.abstract | This paper proposes a genetic algorithm (GA) and constraint satisfaction adaptive neural network (CSANN) hybrid approach for job-shop scheduling problems. In the hybrid approach, GA is used to iterate for searching optimal solutions, CSANN is used to obtain feasible solutions during the iteration of genetic algorithm. Simulations have shown the valid performance of the proposed hybrid approach for job-shop scheduling with respect to the quality of solutions and the speed of calculation. | en_US |
| dc.description.sponsorship | This research is supported by the National Nature Science Foundation and National High -Tech Program of P. R. China. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | ACTA Press | en_US |
| dc.subject | Job-shop scheduling | en_US |
| dc.subject | Genetic algorithm | en_US |
| dc.subject | Neural network | en_US |
| dc.title | Genetic algorithm and neural network hybrid approach for job-shop scheduling | en_US |
| dc.type | Conference Paper | 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: | Publications Computer Science Dept of Computer Science Research Papers | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Fulltext.pdf | 65.33 kB | Adobe PDF | View/Open |
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