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

Authors

  • 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

DOI:

https://doi.org/10.24215/16666038.20.e03

Keywords:

Cooling Schedule, Optimization, Sensor networks, Simulated Annealing

Abstract

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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Published

2020-05-26

Issue

Section

Original Articles

How to Cite

[1]
“Tuning a hybrid SA based algorithm applied to Optimal Sensor Network Design”, JCS&T, vol. 20, no. 1, p. e03, May 2020, doi: 10.24215/16666038.20.e03.

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