Multiobjective Optimization using Parallel Vector Evaluated Particle Swarm Optimization

K.E. Parsopoulos, D.K. Tasoulis, and M.N. Vrahatis (Greece)


Particle Swarm Optimization, Multiobjective Optimiza tion, PVM


This paper studies a parallel version of the Vector Eval uated Particle Swarm Optimization (VEPSO) method for multiobjective problems. Experiments on well known and widely used test problems are performed, aiming at inves tigating both the efficiency of VEPSO as well as the advan tages of the parallel implementation. The obtained results are compared with the corresponding results of the Vector Evaluated Genetic Algorithm approach, yielding the supe riority of VEPSO.

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