A Particle Swarm Optimization Based on Multi Objective Functions with Uniform Design

Abstract

A Multi-objective problems occurs wherever optimal solution necessary to be taken in the presence of tradeoffs between more than one conflicting objectives. Usually the population's values of MOPSO algorithm are random which leads to random search quality. Particle Swarm Optimization Based on Multi Objective Functions with Uniform Design (MOPSO-UD), is proposed to enhance the accuracy of the particles convergence and keep the versatility of the Pareto optimal solutions and used the Uniform design to resolve the randomize search problem of the original MOPSO algorithm also the execution time of MOPSO-UD is faster compared with multi-objective particle swarm optimization algorithm (MOPSO).