Evolutionary multi-objective approach for solving robust optimization problem

Robust Optimization Problem(ROP) is one of the most important parts of Evolutionary Multiobjective Optimiza-tion(EMO).For most practical engineering optimization problems,the aim of them is to obtain robust optimal solutions.In this paper,the concept of Pareto in multiobjective optimization is employed to deal simultaneously with robustness and opti-mality.Therefore,a ROP is transformed into a biobjective problem,one of which is the robustness of solution and the other is the optimality of solution.Combining the characteristics of ROP and multi-objective optimization,a Multi-Objective Evolu-tionary Algorithm(MOEA) for solving ROPs is designed by dynamic weight strategy.By the several experiments on two ROP test problems,the results demonstrate that the proposed evolutionary multi-objective approach is efficient.