Naval Wholesale Inventory Optimization
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Authors
Salmerón, Javier
Craparo, Emily
Subjects
Advisors
Date of Issue
2019
Date
Publisher
Springer
Language
Abstract
The U.S. Naval Supply Systems Command (NAVSUP), Weapon Systems Support, manages an inventory of approximately 400,000 maritime and aviation line items valued at over $20 billion. This work describes NAVSUP’s Wholesale Inventory Optimization Model (WIOM), which helps NAVSUP’s planners establish inventory levels. Under certain assumptions, WIOM determines optimal reorder points (ROPs) to minimize expected shortfalls from fill rate targets and deviations from legacy solutions. Each item’s demand is modeled probabilistically, and negative expected deviations from target fill rates are penalized with nonlinear terms (conveniently approximated by piecewise linear functions). WIOM’s solution obeys a budget constraint. The optimal ROPs and related expected safety stock levels are used by NAVSUP’s Enterprise Resource Planning system to trigger requisitions for procurement and/or repair of items based on forecasted demand. WIOM solves cases with up to 20,000 simultaneous items using both a direct method and Lagrangian relaxation. In particular, this proves to be more efficient in certain cases that would otherwise take many hours to produce a solution.
Type
Book Chapter
Description
The article of record as published may be found at https://doi.org/10.1007/978-3-030-28565-4_15
Series/Report No
Department
Operations Research (OR)
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
Sponsors
Funder
Format
17 p.
Citation
Salmeron J., Craparo E.M. (2019) Naval Wholesale Inventory Optimization. In: Fathi M., Khakifirooz M., Pardalos P. (eds) Optimization in Large Scale Problems. Springer Optimization and Its Applications, vol 152. Springer, Cham.
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.