A New Robust Scheduling Model for Permutation Flow Shop Problem

As traditional flow shop scheduling model is usually designed for deterministic production environment and under single optimization objective, this paper considers a permutation flow shop scheduling problem with uncertain processing time so as to overcome the deficiency. Moreover, a multi-objective robust scheduling model is constructed to minimize the tardiness and total completion time under min-max regret criterion. Directed graph is used to analyze the scenario of the maximum regret value scenario (i.e. the worst-case scenario). Finally, genetic algorithm is applied to solve this robust scheduling model. Through the experimental simulation results, the proposed model shows its efficiency and effectiveness.