A Particle Swarm Optimization Algorithm for Robust Flow-shop Scheduling with Fuzzy Processing Times

This paper discusses a kind of flow-shop scheduling problems (FSSPs) with uncertain processing times. The uncertain processing times are represented by triangular fuzzy numbers. An integrated objective function is designed to embody the schedule bi-criteria, which involves the fuzzy makespan and the robustness of makespan. The robustness of makespan is measured by the spread of makespan. A particle swarm optimization (PSO) algorithm is developed to solve the robust FSSP. Extensive experiments were performed to test the parameters of PSO and to compare the PSO with a genetic algorithm (GA). The computational results show that such a PSO algorithm is effective for our problems and outperforms the GA.