Artículo

CGD-GA: A graph-based genetic algorithm for sensor network design

Carballido, Jessica Andrea Icon; Ponzoni, Ignacio Icon; Brignole, Nélida Beatriz Icon

Otros responsables

Fecha

2007-11-02

Editorial

Elsevier Science Inc

Revista

Information Sciences

Título del libro

Nombre del evento

Fecha del evento

Institución organizadora

ISSN

0020-0255

eISSN

ISBN

Idioma

Inglés

Tipo del evento

Clasificación temática

Resumen

The foundations and implementation of a genetic algorithm (GA) for instrumentation purposes are presented in this paper. The GA constitutes an initialization module of a decision support system for sensor network design. The method development entailed the definition of the individual's representation as well as the design of a graph-based fitness function, along with the formulation of several other ad hoc implemented features. The performance and effectiveness of the GA were assessed by initializing the instrumentation design of an ammonia synthesis plant. The initialization provided by the GA succeeded in accelerating the sensor network design procedures. It also accomplished a great improvement in the overall quality of the resulting instrument configuration. Therefore, the GA constitutes a valuable tool for the treatment of real industrial problems.

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Licencia Creative Commons

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