Robust and satisfactory Job Shop scheduling under fuzzy processing times and flexible due dates

The earliness/tardiness Job Shop scheduling problems (JSSPs) with fuzzy processing times and the objective of minimizing the makespan is discussed in this paper. The requirement for the due date of the product is flexible and is described by trapezoidal fuzzy number. On the basis of qualitative possibility theory, a measure of schedule robustness is defined to optimize the worst-case performance. The robust optimization criterion is established by combining the robustness measure and the satisfaction degree for the most plausible performance. A genetic simulated-annealing algorithm is used to solve the fuzzy robust JSSPs. An extensive experiment was conducted to testify the effectiveness of the used algorithm and to demonstrate the advantages of the proposed robust optimization model.