Finding the optimal CSP inventory level for multi-echelon system in Air Force using random effects regression model

Kyung Bok Yoon, So Young Sohn

Research output: Contribution to journalArticle

20 Citations (Scopus)

Abstract

Determining the optimal inventory level of CSP (concurrent spare parts) is crucial at the time of acquisition of new aircrafts. Most of the existing optimal CSP models do not take into account the time varying characteristics of CSP even though their demand rates are sensitive to such variation. In this paper, we introduce the CSP inventory model using a two stage approach. At the first stage, we use a random effects model to predict the expected demand of CSP in a multi-echelon system consisting of depot and bases based on CSPs varying characteristics with time. At the second stage, we find the optimal inventory level of CSP by using the optimization algorithm with various constraints under limited budget. The study is expected to contribute to the Air Force establishing the optimal national defense procurement policy for CSP of aircrafts.

Original languageEnglish
Pages (from-to)1076-1085
Number of pages10
JournalEuropean Journal of Operational Research
Volume180
Issue number3
DOIs
Publication statusPublished - 2007 Aug 1

Fingerprint

Multi-echelon
Spare Parts
air force
Random Effects Model
Concurrent
Regression Model
regression
aircraft
Air
Aircraft
demand
budget
Inventory Model
time
Spare parts
Multi-echelon systems
Regression model
Random effects
Optimization Algorithm
Time-varying

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Modelling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management

Cite this

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Finding the optimal CSP inventory level for multi-echelon system in Air Force using random effects regression model. / Yoon, Kyung Bok; Sohn, So Young.

In: European Journal of Operational Research, Vol. 180, No. 3, 01.08.2007, p. 1076-1085.

Research output: Contribution to journalArticle

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