Simulation-based optimization methods for setting production planning parameters

This paper refers to a hierarchical production planning system in a make-to-order environment. A challenging task in this context is to determine good production parameter settings in order to benefit from established planning methods. We present a framework for hierarchical production planning which we use to identify good settings for three planning parameters, namely planned leadtimes, safety stock, and lotsizes. Within a discrete-event simulation which mimics the production system we use a mathematical optimization model for replicating the decision problem. This mathematical model is solved to optimality using a standard optimization engine. We use data referring to four different demand market situations in order to derive general statements concerning the quality and sensitivity of the three analyzed planning parameters.