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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Queiroz dos Santos, J.P. de Lima, F.C. Magalhaes, R.M. de Melo, J.D. Neto, A.D.D. |
| Copyright Year | 2009 |
| Description | Author affiliation: Department of Computing of the State University of Rio Grande do Norte and College of Science and Technology Mater Christi, Brazil (de Lima, F.C.) || Department of Automation and Control, of the Federal University of Rio Grande do Norte, Brazil (Queiroz dos Santos, J.P.; Magalhaes, R.M.; de Melo, J.D.; Neto, A.D.D.) |
| Abstract | In the process of searching for better solutions, a metaheuristic can be guided to regions of promising solutions using the acquisition of information on the problem under study. In this work this is done through the use of reinforcement learning. The performance of a metaheuristic can also be improved using multiple search trajectories, which act competitively and/or cooperatively. This can be accomplished using parallel processing. Thus, in this paper we propose a hybrid parallel implementation for the GRASP metaheuristics and the genetic algorithm, using reinforcement learning, applied to the symmetric traveling salesman problem. |
| Starting Page | 2798 |
| Ending Page | 2803 |
| File Size | 1859532 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424435487 |
| ISSN | 10987576 |
| DOI | 10.1109/IJCNN.2009.5178938 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-06-14 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Genetic algorithms Learning Parallel processing Traveling salesman problems Neural networks Large-scale systems Context modeling Stochastic processes Power generation |
| Content Type | Text |
| Resource Type | Article |
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