A new approach to site demand-based level inventory optimization

Abstract

Naval Supply Systems Command (NAVSUP) supports Navy, Marine Corps, Joint and Allied Forces with their inventory of more than 430,000 items worth $21 billion using several distribution sites. Choosing the optimum order-point and order-quantity for each item is important to meet the stochastic demand while satisfying multiple restrictions such as budget and maximum number of orders. The Site Demand-Based Level Inventory Optimization Model (SIOM) is a mixed-integer, linear program developed at the Naval Postgraduate School to provide NAVSUP planners with guidance on this complex problem. Ongoing tests have been successful, but SIOM's computational run times are long. This thesis introduces a new, faster reformulation (SIOMsQ) that approximates the solution of the same problem by reducing the possible candidate sets of order-points and order-quantities for each item. We find that the solutions suggested by SIOMsQ are better than or very close to those of SIOM in test cases provided by NAVSUP, with substantially shorter computational times. Therefore, we recommend using SIOMsQ versus SIOM.