Abstract
This paper proposes a tabu based algorithm to find the Pareto solutions of multiobjective optimizations of electromagnetic devices. An intensification phase by using the evolution algorithm is introduced to ensure the power and efficiency of the proposed method to find the Pareto optimal; and the ranking selecting approach, together with the new neighborhood generation scheme, is proposed to guarantee the diversity of the algorithm, i.e., to have the ability of uniformly sampling the Pareto front. Two numerical examples are reported to demonstrate the abilities of the proposed algorithm for both obtaining and uniformly sampling the Pareto optimal front of the multiobjective design problems.