Particle Swarm Optimization (PSO) and Its Use for ELD

Abstract

Particle swarm optimization (PSO) is a biologically inspired computational search and optimization method developed by Eberhart and Kennedy in 1995 based on the social behaviors of birds flocking and fish schooling. Optimization is the method which is used to find the maximum or minimum value of a function or a process. PSO optimizes the nonlinear function. It was inspired by the helping nature of particle (birds, fishes) while searching for food. This social system was stimulated for the development of this approach. PSO approach produces high-quality solution in small time and fast convergence. In this process, particles fly in the space and search the food. They search the food by their own experience and also use the experience of nearby particles. Particles use the best position find by them along with their neighbor also. This social behavior is taken as an optimization tool in soft computing.

Keywords: algorithm, data, particle string, ELD, ontogeny, optimization, particle swarm, velocity constraints