Genetic algorithm and adaptive neural network hybrid method for job-shop scheduling problems
| dc.cclicence | N/A | en |
| dc.contributor.author | Yang, Shengxiang | |
| dc.contributor.author | Wang, Dingwei | |
| dc.date.acceptance | 1998-02 | |
| dc.date.accessioned | 2020-05-19T14:24:49Z | |
| dc.date.available | 2020-05-19T14:24:49Z | |
| dc.date.issued | 1998-07 | |
| dc.description | The file attached to this record is the author's final peer reviewed version. | en |
| dc.description.abstract | This paper proposes a hybrid method of genetic algorithm (GA) and constraint satisfaction adaptive neural network (CSANN) for solving job-shop scheduling problems. In the hybrid method GA is used to iterate for searching optimal solutions, CSANN is used to solve feasible solutions during the iteration of GA. Computer simulations have shown the good performance of the proposed hybrid method for job-shop scheduling problems. | en |
| dc.funder | Other external funder (please detail below) | en |
| dc.funder.other | National Natural Science Foundation of China | en |
| dc.identifier.citation | Yang, S. and Wang, D. (1998) Genetic algorithm and adaptive neural network hybrid method for job-shop scheduling problems. Control and Decision, 13(Supplement), pp.402-407. | en |
| dc.identifier.issn | 1001-0920 | |
| dc.identifier.uri | https://dora.dmu.ac.uk/handle/2086/19618 | |
| dc.language.iso | zh | en |
| dc.peerreviewed | Yes | en |
| dc.projectid | 69684005 | en |
| dc.publisher | Northeastern University Press, China | en |
| dc.researchinstitute | Institute of Artificial Intelligence (IAI) | en |
| dc.subject | Job-shop scheduling | en |
| dc.subject | genetic algorithm | en |
| dc.subject | constraint satisfaction | en |
| dc.subject | adaptive neural network | en |
| dc.title | Genetic algorithm and adaptive neural network hybrid method for job-shop scheduling problems | en |
| dc.type | Article | en |