A Multiobjective Approach of Differential Evolution Optimization Applied to Electromagnetic Problems

The differential evolution (DE) algorithm belongs to a class of evolutionary techniques that use the stochastic approach to solve optimization problems. Storn and Price proposed it in its mono-objective form, and since then it has yielded good results, such as faster global convergence, when compared with other classical evolutionary algorithms. A multi-objective approach is proposed here, combining the DE evolutionary mechanism with concepts extracted from the strength Pareto evolutionary algorithms (SPEAs), proposed by Zitzler and Theile. This approach was applied to test functions and electromagnetic problems to demonstrate its reliability.