Abstract: PSO algorithm with robust solution searching methodologies is proposed，a new mechanism for expected fitness evaluations is introduced，and a strategy for assigning expected fitness only to the best solutions of particles and their neighbors is proposed，in order to reduce the computational requirements for additional sampling points in the process of expected fitness assignments.Moreover，the neighborhood methodology is redefined in accordance with the goal of the proposed algorithm.Two case studies are reported to validate and demonstrate the feasibilities and advantages of using the proposed algorithm in finding the robust solutions.