Experimental research on robust multi-objective evolutionary algorithm
多目标进化算法鲁棒性实验研究*

In optimization studies including multi-objective evolutionary algorithms, the main focus is placed on finding the global optimum or global pareto-optimal solutions. However, in practice,the environment is not static, need to find robust solutions. Due to environmental uncertainly and the lack of suitable test function, multi-objective robust optimization problem is very little research. This paper tested the performance of the algorithm in the presence of the noise through experiments. Experimental results show that the original test function is no longer applicable, need construct robust test function.