Coping with Demand Shocks: A Distribution-Free Algorithm for Solving Newsvendor Problems with Limited Demand Information

Abstract:     
We present a new, robust, and eective algorithm for the multiple-period newsvendor problem when there is little demand information available. In today's competitive market, demand volume and even distribution can change quickly. The algorithm needs only a rough estimate of the lower and upper bounds of demand range; no other knowledge such as the demand mean, variance, or distribution type is necessary. Through simulations we show that our algorithm performs well compared to four other standard newsvendor problem solutions in a variety of situations, except when salvage values are high.

Number of Pages in PDF File: 34

Keywords: Newsvendor Problem; Demand Forecasting; Demand Shocks, Machine Learning Algorithm, Inventory Management, Stochastic Demands.

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