Analog circuits optimization based on evolutionary computation techniques

This paper presents a new design automation tool based on a modified genetic algorithm kernel, in order to increase efficiency on the analog circuit and system design cycle. It combines a robust optimization with corners, machine learning modeling and distributed processing capability able to deal with multi-objective and highly constrained optimization problems. The resulting optimization tool, simulation capabilities, and extensible architecture are presented and the improvement in design productivity is demonstrated for the design of robust CMOS operational amplifiers.