Comparison among evolutionary algorithms and classical optimization methods for circuit design problems

This work concerns the comparison of evolutionary algorithms and standard optimization methods on two circuit design problems: the parameter extraction of device circuit model and the multi-objective optimization of an operational transconductance amplifier. We compare standard optimization techniques and evolutionary algorithms in terms of quality of the solutions and computational effort, that is, objective function evaluations needed to compute them. The experimental results obtained show as standard techniques are robust with respect evolutionary algorithms, while the latter are more effective in terms of the standard metrics and function calls. In particular for the multiobjective problem, the observed Pareto front determined by evolutionary algorithms has a better spread of solutions with a larger number of nondominated solutions with respect to the standard multi-objective techniques.

1 Introduction

In this research work we compare experimentally the effectiveness of evolutionary algorithms and standard optimization techniques. As test bed we used two Circuit Design Problems: parameter extraction of device circuit model and optimization of a Operational Transconductance Amplifier. The first problem faced is a single-objective optimization problem, the latter is a multi-objective optimization prob-lem. Both problems are real world applications which have been supplied by STMICROELECTRONICS.