Simulation-based optimization for integrated production planning and capacity expansion decisions

In this paper, we consider a simplified semiconductor supply chain that consists of a single front-end facility and back-end facility. We present a production planning formulation that is based on clearing functions. A cost-based objective function is considered. The minimum utilization of expensive bottleneck machines in the front-end facility is a parameter of the model. At the same time, the less expensive capacity of the back-end facility can be increased to reduce the cycle time in the back-end facility. The release schedules obtained from the planning formulations are assessed using discrete-event simulation. An overall cycle time larger than a given maximum value is penalized. Simulated annealing is used to determine appropriate minimum utilization levels for the front-end bottleneck machines and appropriate capacity expansion levels for the back-end. The results of the computational experiments demonstrate that the profit can be increased while the maximum possible overall cycle time is not violated.

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