Searching for robust Pareto optimal solutions is one of the most important fields in the research of multi-objective evolutionary algorithm (MOEA).Recently

both traditional MOEA and EFF-MOEA which optimize "original objective function" and "effective objective function" respectively easily lose some kinds of solutions.In order to solve this deficiency

we defined a new robust Pareto optimal solution and proposed a novel MOEA named as MOEA/R

which converts a multi-objective robust optimization problem (MROP) into a bi-objective optimization problem.Each of the two objectives represents a sub-MOP

one optimizes solution’s quality and the other optimizes solution’s robustness.Through the comparison and analysis between MOEA/R

NSGA-Ⅱ and Eff-MOEA

the experimental results demonstrate that MOEA/R can acquire good purposes.The most important contribution of this paper is that MOEA/R explores a novel methodology for searching robust Pareto optimal solutions.