Multiobjective Electromagnetic Optimization Based on a Non-Dominated Sorting Genetic Approach with a Chaotic Crossover Operator

摘要

The Non-dominated Sorting GeneticAlgorithm II (NSGA-II) algorithm is an effective methodology to solve multiobjective optimization problems. A modified NSGA-II to seek the Pareto front of electromagnetic multiobjective design problems is proposed in this paper. We propose the use of chaotic sequences based on Zaslavskii map in NSGA-II crossover operator. The proposed method is tested on TEAM 22 benchmark optimization problem with promising results.