Tuning a hybrid SA based algorithm applied to Optimal Sensor Network Design
| Autor: | Gabriela F. Minetti, José Hernandez, Mercedes Carnero, Carolina Salto, Carlos Bermudez, Mabel Sanchez |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: | |
| Zdroj: | Journal of Computer Science and Technology, Vol 20, Iss 1, Pp e03-e03 (2020) |
| Druh dokumentu: | article |
| ISSN: | 1666-6046 1666-6038 16666038 95580425 |
| DOI: | 10.24215/16666038.20.e03 |
| Popis: | Sensor network design problem (SNDP) in process plants includes the determination of which process variables should be measured to achieve a required degree of knowledge about the plant. We propose to solve the SNDP problem in plants of increasing size and complexity using a hybrid algorithm based on Simulated Annealing (HSA) as main metaheuristic and Tabu Search embedded with Strategic Oscillation (SOTS) as a subordinate metaheuristic. We are researching on the adjustments of its control parameters to obtain the best HSA performance. Experimental results indicate that a high-quality solution in reasonable computational times can be found by HSA effectively. Moreover, HSA shows good features solving SNDP compared with proposals from the literature. |
| Databáze: | Directory of Open Access Journals |
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