Tuning a hybrid SA based algorithm applied to Optimal Sensor Network Design


  • Gabriela F. Minetti Universidad Nacional de La Pampa, Fac. de Ingeniería
  • José Hernandez Grupo de Optimización - Facultad de Ingeniería – Universidad Nacional de Río Cuarto, Rio Cuarto, Argentina
  • Mercedes Carnero Grupo de Optimización - Facultad de Ingeniería – Universidad Nacional de Río Cuarto, Rio Cuarto, Argentina
  • Carolina Salto LISI - Facultad de Ingeniería, Universidad Nacional de La Pampa, General Pico, Argentina
  • Carlos Bermudez LISI - Facultad de Ingeniería, Universidad Nacional de La Pampa, General Pico, Argentina
  • Mabel Sanchez Departamento de Ingeniería Química, Universidad Nacional del Sur (UNS) and Planta Piloto de Ingeniería Química - PLAPIQUI (UNS-CONICET), (8000) Bahía Blanca, Argentina




Cooling Schedule, Optimization, Sensor networks, Simulated Annealing


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.


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How to Cite

Minetti, G. F., Hernandez , J. ., Carnero, M., Salto, C., Bermudez, C., & Sanchez, M. (2020). Tuning a hybrid SA based algorithm applied to Optimal Sensor Network Design. Journal of Computer Science and Technology, 20(1), e03. https://doi.org/10.24215/16666038.20.e03



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