Solution of fractional programming problems using PSO algorithm

Abstract

This paper presents strategy of particle swarm optimization (PSO) algorithm introduced by Kennedy and Eberhart [1] for solving fractional programming problems. Particle swarm optimization (PSO) is a population-based optimization technique, which is an alternative tool to genetic algorithm (GA) and other evolutionary algorithms (EA) and has gained lot of attention in recent years. PSO is a stochastic search technique with reduced memory requirement, computationally effective and easier to implement as compared to EA. In this paper, possibility of using particle swarm optimization algorithm for solving fractional programming problems has been considered. The particle swarm optimization technique has been tried on a set of 12 test problems taken from the literature whose optimal solutions are known. A penalty function approach [2] is incorporated for handling constraints of the problem. Our experiences has shown that it can be effectively used to solve fractional programming problems also.