Multi-Echelon Inventory Systems with Lateral Supply: A Technical Note,

Abstract

Exact analytic solutions to many logistics problems can be obtained only by making unrealistic simplifying assumptions. An alternative is to construct efficient computational techniques that provide close approximations to the solutions of the real problems over a large range of simulated situations. The author chose to take that approach in this analysis of a long-standing and difficult problem. Approximations are developed to estimate the expected backorders in a multiechelon system in which lateral supply actions between bases are allowed when a backorder occurs. These approximations are easy to compute, and the average absolute error is less than 3 percent when items are depot-reparable, even when bases are dissimilar; the average error is nearly 5 percent, however, and the technique is less convincing when items are base-reparable. The average number of units of an item that are in repair and resupply is referred to as the pipeline. The benefit of lateral supply is negligible unless the spares in the system exceed the pipeline, and lateral supply is rarely needed when spares are more than 1.5 to 2 times the pipeline. However, for intermediate spares values, lateral supply provides large improvements in both absolute and percentage terms. Backorder reductions of 30 to 50 percent are not uncommon, and a 72-percent reduction was observed in one case.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1988
Accession Number
ADA193202

Entities

People

  • Craig C. Sherbrooke

Organizations

  • LMI

Tags

Communities of Interest

  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Air Force
  • Confidence Limits
  • Contracts
  • Databases
  • Department Of Defense
  • Equations
  • Errors
  • Information Science
  • Interpolation
  • Intervals
  • Inventory
  • Logistics
  • Logistics Management
  • Pipelines
  • Simulations
  • Supply Chain
  • Supply Depots

Readers

  • Educational Psychology
  • Logistics and Supply Chain Management.
  • Mathematics or Statistics