An Investigation on Basic Concepts of Particle Swarm Optimization algorithm for VLSI Design

Particle Swarm Optimization algorithm is an evolutionary algorithm that has been applied to many different engineering and technological problems with considerable success. Since its first publication is in 1995, it has been continually modified trying to improve its convergence properties. Thus, many variants have been proposed in the literature. Some of these variants were related to a particular problem and had little application outside the field where they have been proposed. These PSO variants have been used to solve a wide range of optimization and inverse problems: continuous, discrete, dynamical, multioptimal, and combinatorial, with and without additional constraints. This paper insisting the importance of the stochastic stability analysis of the particle trajectories in order to achieve convergence and an algorithm for classical particle swarm optimization (PSO) is discussed. Also, it codes in MATLAB environment is included.