Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/44322
Título: Multi-objective genetic algorithms applied to low power pressure microsensor design
Autores/as: Monzón-Verona, José Miguel 
Garcia-Alonso Montoya, Santiago 
Sosa, Javier 
Montiel-Nelson, Juan A. 
Clasificación UNESCO: 3306 Ingeniería y tecnología eléctricas
Palabras clave: Genetic algorithm
Optimization
Low power optimization
Microsensor
Multi-objective, et al.
Fecha de publicación: 2013
Editor/a: 0264-4401
Publicación seriada: Engineering Computations 
Resumen: Purpose – The purpose of this paper is to explain in detail the optimization of the sensitivity versus the power consumption of a pressure microsensor using multi-objective genetic algorithms. Design/methodology/approach – The tradeoff between sensitivity and power consumption is analyzed and the Pareto frontier is identified by using NSGA-II, AMGA-II and ɛ-MOEA methods. Findings – Comparison results demonstrate that NSGA-II provides optimal solutions over the entire design space for spread metric analysis, and AMGA-II is better for convergence metric analysis. Originality/value – This paper provides a new multiobjective optimization tool for the designers of low power pressure microsensors.
URI: http://hdl.handle.net/10553/44322
ISSN: 0264-4401
DOI: 10.1108/EC-03-2012-0072
Fuente: Engineering Computations (Swansea, Wales)[ISSN 0264-4401],v. 30 (17099245), p. 1128-1146
Colección:Artículos
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