An Analysis of a Single Location Inventory Problem for Two Interchangeable Recoverable Items.

Abstract

In this paper we examine the interchangeability/substitutability problem for two recoverable items that fail at a single location. We assume the failure processes for each type of item are independent, stationary Poisson processes. We also assume the repair times are exponentially distributed. Furthermore, we assume that the system is a closed system, that is, no items are added to or deleted from the system. We first consider a discrete-time problem and show that this problem is a Markovian decision problem. We then show that for this problem there exist optimal stationary Markov control policies. Next we formulate a continuous time model and show how to find the optimal stationary Markov control policy using linear programming. Unfortunately, this approach is impractical for solving most real problems. Consequently we have established and explored some of the properties that we feel an optimal policy should possess. A discussion of these properties is given in Section IV. Lastly, we will describe a heuristic that can be used to find a good policy. This method is an efficient simulation search method that finds policies having the properties we conjecture an optimal policy should possess. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1979
Accession Number
ADA067591

Entities

People

  • Carol Shilepsky
  • David Heath
  • John Muckstadt

Organizations

  • Cornell University College of Engineering

Tags

Communities of Interest

  • C4I
  • Materials and Manufacturing Processes
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Circuit Boards
  • Computer Programming
  • Computers
  • Engineering
  • Equations
  • Industrial Engineering
  • Inventory
  • Linear Programming
  • Markov Chains
  • Mathematical Models
  • Models
  • Operations Research
  • Probability
  • Random Variables
  • Simulations
  • Systems Engineering

Fields of Study

  • Mathematics

Readers

  • Logistics and Supply Chain Management.
  • Mathematical Modeling and Probability Theory.