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A simple procedure for determining order quantities under a fill rate constraint and normally distributed lead-time demand
Institution:1. Joseph L. Rotman School of Management, University of Toronto, Toronto, M5S 3E6, Canada;2. Department of Industrial Engineering and Management, Ben Gurion University of the Negev, P.O. 653 Beer Sheva 84105, Israel;1. Dpto. de Matemáticas, Estadística e Investigación Operativa. Universidad de La Laguna, Tenerife, Islas Canarias, Spain;2. Dpto. de Ingeniería Informática y de Sistemas. Universidad de La Laguna, Tenerife, Islas Canarias, Spain;1. MIT Global Scale, MIT-Zaragoza International Logistics Program, Zaragoza Logistics Center, Zaragoza 50197, Spain;2. Combat Development and Integration, U.S. Marine Corps Combat Development Command, Quantico, VA 22134, USA;3. Operations and Supply Chain Management, Opus College of Business, University of St. Thomas, 1000 LaSalle Avenue, Minneapolis, MN 55403-2005, USA;1. Department of Industrial Engineering, Center of excellence in optimization and advanced manufacturing systems, Iran University of Science and Technology, Tehran, Iran;2. School of Railway Engineering, Iran University of Science and Technology, Tehran, Iran;1. Department of Industrial Engineering, Seoul National University, Seoul 151-744, Republic of Korea;2. Department of Industrial Engineering, Pusan National University, Busan 609-735, Republic of Korea;3. Department of Applied Mathematics with Oceanology and Computer Programming, Vidyasagar University, Midnapore 721-102, India
Abstract:One of the most common practical inventory control problems is considered. A single-echelon inventory system is controlled by a continuous review (R, Q) policy. The lead-time demand is normally distributed. We wish to minimize holding and ordering costs under a fill rate constraint. Although, it is not especially complicated to derive the optimal solution, it is much more common in practice to use a simple approximate two-step procedure where the order quantity is determined from a deterministic model in the first step. We provide an alternative, equally simple technique, which is based on the observation that the considered problem for each considered fill rate has a single parameter only. The optimal solution for a grid of parameter values is stored in a file. When solving the problem for an item we use interpolation, or for parameter values outside the grid special approximations. The approximation errors turn out to be negligible. As an alternative to the interpolation we also provide polynomial approximations.
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