Gokhan Metan We present a data-driven forecasting technique with integrated inventory control for seasonal data and compare it to the traditional Holt-Winters algorithm. Results indicate that the data-driven approach achieves a 2-5% improvement in the average regret. CitationTechnical Report, Lehigh University, Department of Industrial and Systems Engineering, Bethlehem, PA.ArticleDownload View PDF
In this work, we investigate the value of information when the decision-maker knows whether a perishable product will be in high, moderate or low demand before placing his order. We derive optimality conditions for the probability of the baseline scenario under symmetric distributions and analyze the impact of the cost parameters on simulation experiments. Our … Read more
Inventory management traditionally assumes the precise knowledge of the underlying demand distribution and a risk-neutral manager. New product introduction does not fit this framework because (i) not enough information is available to compute probabilities and (ii) managers are generally risk-averse. In this work, we analyze the value of information for two-stage inventory management in a … Read more