Initial Sensor Network Design with a Multi-Objective Genetic Algorithm

Autores/as

  • Jessica Carballido Universidad Nacional del Sur, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina
  • Ignacio Ponzoni Universidad Nacional del Sur, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina
  • Nélida B. Brignole Universidad Nacional del Sur, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina

Palabras clave:

Multi-Objective Optimization, Genetic Algorithm, Sensor Network Design

Resumen

A Multi-Objective Genetic Algorithm (MOGA) application, which is based on the aggregating approach, is proposed in this article. Its aim is to find a consistent instrument configuration for industrial process plants that will constitute a convenient initial set of input data for structural Observability Analysis Algorithms (OAs). The better this configuration is, the faster the OAs will converge to a satisfactory solution. Algorithmic effectiveness was evaluated through the analysis of small academic case studies. The results obtained through our algorithm show excellent performance. Therefore, it can be stated that the prototype presented in this work is good enough to serve as a sound basis for the development of the definitive MOGA module, whose implementation will support large-size industrial plant models.

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Publicado

2004-08-03

Cómo citar

Carballido, J., Ponzoni, I., & Brignole, N. B. (2004). Initial Sensor Network Design with a Multi-Objective Genetic Algorithm. SADIO Electronic Journal of Informatics and Operations Research, 6, 34-41. https://revistas.unlp.edu.ar/ejs/article/view/17529