Multi-objective Optimization Using Modified Particle Swarm

This paper presents a new algorithm solving multiple-objective optimization problems with particle swarm method. We use an extended memory forrecording non-dominated solutions found along the algorithm run .The Crossover operator is used to compute the velocity of particles. We also use theturbulence factor in this algorithm that has great effect on the convergence of the algorithm. The integrity of this algorithm is validated by testing it on 6 benchmark problems.

Keywords:

Multiobjective Optimization , Particle Swarm Optimization , Optimization