Photolithography is typically the bottleneck process in semiconductor manufacturing. In this thesis, we present a model for optimizing photolithography job scheduling in the presence of both individual and cluster tools. The combination of individual and cluster tools that process various layers or stages of the semiconductor manufacturing process flow is a special type of flexible flowshop. We seek separately to minimize total weighted completion time and maximize on-time delivery performance. Experimental results suggest that our mathematical- and heuristic-based solution approaches show promise for real world implementation as they can help to improve resource utilization, reduce job completion times, and decrease unnecessary delays in a wafer fab
