This study considers a scheduling problem for a flow shop with urgent jobs and limited waiting times.The urgent jobs and limited waiting times are major considerations for scheduling in semiconductor manufacturing systems.The objective function is to minimize a weighted sum hassan haskins hurdle of total tardiness of urgent jobs and the makespan of normal jobs.
This problem is formulated in mixed integer programming (MIP).By using a commercial optimization solver, the MIP can be used to find an optimal solution.However, because this problem is proved to be NP-hard, solving to optimality requires a significantly long computation time for a practical size problem.
Therefore, this study adopts metaheuristic algorithms to obtain a good solution quickly.To complete this, two metaheuristic algorithms (an iterated circuiteer ii blower greedy algorithm and a simulated annealing algorithm) are proposed, and a series of computational experiments were performed to examine the effectiveness and efficiency of the proposed algorithms.