A Multiobjective Gaussian Particle Swarm Approach Applied to Electromagnetic Optimization

The development of optimization techniques for multiobjective problems in electromagnetics has been flourishing in the last decade. This paper proposes an improved multiobjective particle swarm optimization approach and applies it to the multiobjective version of TEAM workshop problem 22. Simulation results show that this improved version of the algorithm finds a better Pareto-optimal front with respect to more classical PSO methods while maintaining a better spread of nondominated solutions along the front. Furthermore, the proposed algorithm is compared with the widely used Nondominated Sorting Genetic Algorithm-II (NSGA-II) method highlighting a strongly different behaviour of these strategies.