Events
AdONE Seminar: Reha Uzsoy (North Carolina State University)
This talk will present a body of work that seeks to link the two areas of inventory management and production planning. Since the underlying stochastic optimization problem is complex, rendering exact solutions impractical, we seek to obtain approximate solutions using simple linear programming models that i) account for queueing behavior in the production system, specifically workload-dependent lead times, and, ii) use chance constraints to maintain appropriate safety stocks in the face of stochastic demand. Recognizing that most production systems are driven by forecasts that are updated as information evolves, we use the Martingale Model of Forecast Evaluation as a demand model to derive the chance constraints. Extensive computational experiments in several different environments show promising results and indicate directions for further improvements.