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

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

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)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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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