Min-max regret criterion-based robust model for the permutation flow-shop scheduling problem

This article studies the permutation flow-shop scheduling problem (PFSP) with interval production time. A min-max regret criterion-based robust scheduling model is established by taking both the robustness of total completion time and the tardiness of production into consideration simultaneously. To decrease the infinite number of scenarios to a limited level, a directed graph tool is applied to conduct worst case scenario analysis. In addition, since the PFSP is proved to be NP hard, a genetic algorithm is implemented to solve this robust scheduling model. Experimental simulation results verify the effectiveness and efficiency of this model. Moreover, it could cover the drawback of the traditional uncertain scheduling models, which consider only the robustness of total completion time. This could help manufacturing enterprises to increase time delivery capability so as to enhance downstream customers' satisfaction.