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Modelling and computing (Rn, Sn) policies for inventory systems with non-stationary stochastic demand
Institution:1. School of Business Administration, Northeastern University, Shenyang, Liaoning 110167, China;2. Department of Management Science and Statistics, University of Texas at San Antonio, San Antonio. TX 78249-0634, USA;3. Lee Kong Chian School of Business, Singapore Management University, Singapore 178899, Singapore;1. Technische Universiteit Eindhoven, P.O. Box 513, EINDHOVEN 5600 MB, Netherlands;2. Volkswagen AG, Dr. Rudolf-Leiding-Platz 1, Baunatal 34225, Germany;3. IBM Research, Saeumerstrasse 4, Rueschlikon 8803, Switzerland;4. School of Management, Technical University of Munich, Munich 80333, Germany;5. Universität Bayreuth, Bayreuth 95440, Germany
Abstract:This paper addresses the single-item, non-stationary stochastic demand inventory control problem under the non-stationary (R, S) policy. In non-stationary (R, S) policies two sets of control parameters—the review intervals, which are not necessarily equal, and the order-up-to-levels for replenishment periods—are fixed at the beginning of the planning horizon to minimize the expected total cost. It is assumed that the total cost is comprised of fixed ordering costs and proportional direct item, inventory holding and shortage costs. With the common assumption that the actual demand per period is a normally distributed random variable about some forecast value, a certainty equivalent mixed integer linear programming model is developed for computing policy parameters. The model is obtained by means of a piecewise linear approximation to the non-linear terms in the cost function. Numerical examples are provided.
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