Tuning a hybrid SA based algorithm applied to Optimal Sensor Network Design
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 o...
Guardado en:
| Autores principales: | , , , , , |
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| Formato: | Articulo |
| Lenguaje: | Inglés |
| Publicado: |
2020
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| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/97201 |
| Aporte de: |
| Sumario: | 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 studied the tuning of control parameters in order to improve the 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. |
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