Expeditionary Logistics Warehouse Inventory Optimization

Abstract

The Personal Gear Issue (PGI) Division at each Expeditionary Support Unit is responsible for ordering, inventory management, and distribution of all personal gear issued. This work adapts an existing optimization model to determine appropriate ordering policies, specifically, the order point, s, and order quantity, Q, for each line item. The model seeks to minimize cost of inventory subject to target fill rate for each item, maximum number of orders per month, and other constraints. We consider realistic conditions such as current demand, 90 orders per month, and 99 percent fill rate. Under these conditions, the optimal s and Q values result in a significant reduction in the cost of inventory, from $8.2M (current PGIs inventory value) down to $1.23M. In addition, our model shows, via sensitivity analysis, the effect that varying fill-rate targets, monthly order limit, and demand have on cost. For example, we observe a nonlinear increase in cost as a function of demand increase. We recommend that PGI Division revises its ordering policy to include formal optimization analysis and to periodically track demand in order to re-evaluate the optimal s and Q values.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2018
Accession Number
AD1065356

Entities

People

  • Charles M. Deibler

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Biomedical
  • Counter IED
  • Weapons Technologies

DTIC Thesaurus Topics

  • California
  • Costs
  • Equations
  • Explosive Ordnance Disposal
  • Financial Management
  • Inventory
  • Inventory Control
  • Lead Time
  • Linear Programming
  • Logistics
  • Logistics Support
  • Maintenance
  • Management Personnel
  • Mathematical Models
  • Mathematical Programming
  • Models
  • Operations Research
  • Optimization
  • Procurement
  • Sensitivity
  • Simulations
  • Supply Chain
  • Supply Chain Management
  • Tablet Computers
  • United States
  • Warehouses

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Logistics and Supply Chain Management.