Simulation based multiobjective schedule optimization in semiconductor manufacturing

In semiconductor manufacturing, it requires more than one objective such as cycle time, machine utilization and due date accuracy to be kept in focus simultaneously, while developing an effective scheduling. In this paper, a near optimal solution, which is not inferior to any other feasible solutions in terms of all objectives, is generated with a combination of the analytically optimal and simulation based scheduling approach. First, the job shop scheduling problem is modeled using the discrete event simulation approach and the problem is divided in to simulation clock based lot selection sub-problems. Then, at each decision instant in simulated time, a Pareto optimal lot is selected using the various techniques to deal with multiobjective optimization such as weighted aggregation approach, global criterion method, minimum deviation method, and compromise programming. An illustration shows how these techniques work effectively in solving the multiobjective scheduling problem using discrete event simulation.