Multi-objective genetic algorithms applied to low power pressure microsensor design

– 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.

– 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.

– 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.

– This paper provides a new multiobjective optimization tool for the designers of low power pressure microsensors.