Algorithms 2009, 2(1), 259-281; doi:10.3390/a2010259
Article

Design of Sensor Networks for Chemical Plants Based on Meta-Heuristics

1 Dpto. de Ciencias Básicas, Facultad de Ingeniería, Universidad Nacional de Río Cuarto, Campus Universitario, (5800) Río Cuarto, Argentina 2 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
(This article belongs to the Special Issue Sensor Algorithms)
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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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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.

AMA Style

Carnero M, Hernández JL, Sánchez MC. Design of Sensor Networks for Chemical Plants Based on Meta-Heuristics. Algorithms. 2009; 2(1):259-281.

Chicago/Turabian Style

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.

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