Evolutionary Optimization Techniques in Analog Integrated Circuit Designs

Abstract

The proposed genetic algorithm (GA) and particle swarm optimization (PSO) applied for the optimal design of a one-stage operational amplifier circuit with a current mirror load are studied in this work. The sizes of transistors are optimized using the proposed GA and PSO for improved areas and performance parameters of the circuit. A number of performance parameters are collected from the data set created by GA and PSO to optimize the size of transistors and other design parameters. The Spectre simulator is chosen for the simulation of circuit parameters to obtain necessary for the GA and PSO algorithm. Post-optimization results justify that the proposed GA and PSO methods are competitive with differential evolution regarding convergence speed, design specifications, and the optimal CMOS one-stage operational amplifier circuit parameters.