In this paper, an effective method of system modeling and dynamic scheduling to improve operation and control for the Back-End process of semiconductor manufacturing is developed by using Colored Timed Petri-Nets (CTPNs). The simulator of a CTPNs model was utilized to generate a new heuristic scheduling method with genetic algorithm(GA) which enables us to obtain the optimal values of the weighted delay time and standard deviation of lead time.

This paper presents a fuzzy optimization based scheduling method for the manufacturing systems with uncertain production capacities. To address the uncertainties efficiently, the fuzzy optimization technique is used in defining the scheduling problem. Based on the symmetric approach of fuzzy optimization and Lagrangian relaxation technique, a practical fuzzy-optimization based algorithm is developed. The computational experiments based on the real factory data demonstrate that the proposed method provides robust scheduling to hedge against uncertainties.