Design of symmetric switching CMOS inverter using PSOCFIWA

In this paper, symmetric switching characteristics of CMOS inverter are realized using an evolutionary optimization technique called Particle Swarm Optimization with Constriction Factor and Inertia Weight Approach (PSO-CFIWA). PSO-CFIWA is an improved particle swarm optimization (PSO) that proposes a new definition for the velocity vector and swarm updating and hence the solution quality is improved. The performance of PSO-CFIWA is studied with the comparison of real coded genetic algorithm (RGA), a conventional PSO reported in the literature. PSO-CFIWA based design results have been compared also to those of the PSPICE results. The comparative simulation results show that the PSO-CFIWA is superior to other aforementioned evolutionary algorithms for the employed examples and can be efficiently used for CMOS inverter design.