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Design of Sensor Networks for Chemical Plants Based on Meta-Heuristics
Dpto. de Ciencias Básicas, Facultad de Ingeniería, Universidad Nacional de Río Cuarto, Campus Universitario, (5800) Río Cuarto, Argentina
Planta Piloto de Ingeniería Química (UNS-CONICET), Camino La Carrindanga Km 7, (8000) Bahía Blanca, Argentina
* Author to whom correspondence should be addressed.
Received: 3 November 2008; in revised form: 8 January 2009 / Accepted: 17 February 2009 / Published: 20 February 2009
Abstract: In this work the optimal design of sensor networks for chemical plants is addressed using stochastic optimization strategies. The problem consists in selecting the type, number and location of new sensors that provide the required quantity and quality of process information. Ad-hoc strategies based on Tabu Search, Scatter Search and Population Based Incremental Learning Algorithms are proposed. Regarding Tabu Search, the intensification and diversification capabilities of the technique are enhanced using Path Relinking. The strategies are applied for solving minimum cost design problems subject to quality constraints on variable estimates, and their performances are compared.
Keywords: Sensor location; Stochastic optimization; Tabu search; Scatter search; Population based incremental learning algorithms
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Cite This Article
MDPI and ACS Style
Carnero, M.; Hernández, J.L.; Sánchez, M.C. Design of Sensor Networks for Chemical Plants Based on Meta-Heuristics. Algorithms 2009, 2, 259-281.
Carnero M, Hernández JL, Sánchez MC. Design of Sensor Networks for Chemical Plants Based on Meta-Heuristics. Algorithms. 2009; 2(1):259-281.
Carnero, Mercedes; Hernández, José L.; Sánchez, Mabel C. 2009. "Design of Sensor Networks for Chemical Plants Based on Meta-Heuristics." Algorithms 2, no. 1: 259-281.