Sequential multi-objective optimization method for electromagnetic inverse problems

Abstract

Sequential multiobjective optimization method based on radial basis function model is presented in this work to deal with the multiobjective design and optimization problems of engineering electromagnetic devices. Firstly, the initial sample set can be generated by using the sequential optimization method (SOM). SOM can greatly reduce the sample size by integrating the advantages of optimization algorithms and approximate models. Secondly, the optimal Pareto solutions of the multiobjective design problems can be obtained by updating the samples and approximate models sequentially. Thereafter, we calculate the root mean square error for each objective to determine whether it has achieved the default value. Finally, to illustrate the performance of the new method, a classic mathematic test function and a design example of permanent magnet synchronous machine are investigated. It can be found that the proposed method combined the advantages of effectiveness of sequential optimization strategy and lower computation cost of approximate models. The obtained solutions are satisfactory while the computation cost of finite element analysis needed by the new method is less than 1/5 compare with that of direct optimization algorithm.