关键词: 多目标优化设计, Pareto解集, Kriging模型, 期望超体积改进, 可行性概率, 条件模拟

Abstract: To improve the efficiency of multi-objective design optimization of black-box systems,an improved multi-objective optimization algorithm was proposed based on Kriging model,expected hypervolume improvement and probability of feasibility.The feasible region identifying criterion of the algorithm that including the distances between trial points was also effective for the disconnected feasible sub-regions.A Pareto set improvement criterion was proposed which optimized the expected hypervolume improvement and the probability of feasibility simultaneously to strike a balance between improving the optimal solutions and validating the boundary of the feasible region.A convergence assessment method was proposed based on conditional simulation and random set theory,which didn't depend on the real solution set.The proposed algorithm was tested on typical benchmarks and compared with existed algorithms,and the numerical results indicated that the proposed algorithm was very efficient and useful for convergence assessment.

Key words: multi-objective design optimization, Pareto set, Kriging model, expected hypervolume improvement, probability of feasibility, conditional simulation