A Simulation of Alternatives for Wholesale Inventory Replenishment

Abstract

The Navy Supply Systems Command holds $21 billion of inventory across 430,000 repair part line items in support of ongoing naval operations. Selecting the correct reorder point for each of those line items requires a careful balance between tying up precious funding by holding too much inventory that may not be issued, and not holding enough inventory to meet customer demands in a timely fashion. This thesis compares three different methods for selecting the reorder point. The first method is a calculation that offers no attempt at optimization but is simple to understand. The second method is provided by a contractor and uses some optimization with unknown algorithmic details. The last method is a mixed-integer, linear optimization model. Comparative Inventory Simulation, a discrete event simulation model, is designed to find fill rates achieved for each National Item Identification Number under the different reorder methods. We find that average fill rates are higher in 22 out of 24 cases, and average backorder lengths are up to 50% shorter, using the last method.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2016
Accession Number
AD1027582

Entities

People

  • Geoffrey F. Roth

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Computer Languages
  • Computer Programs
  • Computers
  • Data Sets
  • Digital Data
  • Distribution Functions
  • Experimental Design
  • Factorial Design
  • Graphical User Interface
  • Inventory
  • Lead Time
  • Linear Programming
  • Literature Surveys
  • Naval Operations
  • New York
  • Operations Research
  • Optimization
  • Probability
  • Probability Distribution Functions
  • Probability Distributions
  • Scheduling (Production)
  • Simulations
  • Statistical Analysis
  • Steady State
  • United States

Readers

  • Computational Modeling and Simulation
  • Logistics and Supply Chain Management.
  • Operations Research