Circuit Synthesis Using Particle Swarm Optimization

Abstract

Particle swarm optimization (PSO) is a population-based search algorithm that is initialized with a population of random solutions, called particles. In a PSO scheme each particle flies through the search space with a velocity that is adjusted dynamically according with its historical behavior. Therefore, the particles have a tendency to fly towards the best search area along the search process. PSO is also an evolutionary computation technique well adapted to the automatic design of electronic devices. In this line of thought, this paper proposes a PSO based algorithm for logic circuit synthesis. The results show the statistical characteristics of this algorithm with respect to number of generations required to achieve the solutions. The results are compared with other two evolutionary algorithms (EAs), namely genetic and memetic algorithms (GA and MA).