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Dynamic Modelling of Inventories Subject to Obsolescence

A class of models for optimizing inventory costs is presented which takes account of stochastic obsolescence of an inventory item. Obsolescence is defined as a demand state, in such a fashion as to permit appraisal, ex ante, of the probability of arrival of obsolescence at future times, under the as... Full description

Journal Title: Management Science 1 September 1964, Vol.11(1), pp.51-63
Main Author: Brown, George W.
Other Authors: Lu, John Y. , Wolfson, Robert J.
Format: Electronic Article Electronic Article
Language: English
Subjects:
Quelle: Archival Journals (JSTOR)
ID: ISSN: 00251909 ; E-ISSN: 15265501
Link: https://www.jstor.org/stable/2627992
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recordid: jstor_archive_42627992
title: Dynamic Modelling of Inventories Subject to Obsolescence
format: Article
creator:
  • Brown, George W.
  • Lu, John Y.
  • Wolfson, Robert J.
subjects:
  • Economics -- Microeconomics -- Economic costs and benefits
  • Business -- Accountancy -- Financial accounting
  • Philosophy -- Epistemology -- Knowledge
  • Economics -- Microeconomics -- Economic costs and benefits
  • Mathematics -- Applied mathematics -- Statistics
  • Mathematics -- Pure mathematics -- Probability theory
  • Business -- Business economics -- Commercial production
  • Mathematics -- Pure mathematics -- Probability theory
  • Mathematics -- Applied mathematics -- Statistics
  • Social sciences -- Population studies -- Mortality
ispartof: Management Science, 1 September 1964, Vol.11(1), pp.51-63
description: A class of models for optimizing inventory costs is presented which takes account of stochastic obsolescence of an inventory item. Obsolescence is defined as a demand state, in such a fashion as to permit appraisal, ex ante, of the probability of arrival of obsolescence at future times, under the assumption that there are many possible states of demand. Response to obsolescence is introduced by means of a Bayesian procedure. In the most complete model this is done by modification of the state probability vector of a Markov process. Optimization is accomplished by means of a dynamic program.
language: eng
source: Archival Journals (JSTOR)
identifier: ISSN: 00251909 ; E-ISSN: 15265501
fulltext: fulltext
issn:
  • 0025-1909
  • 00251909
  • 1526-5501
  • 15265501
url: Link


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titleDynamic Modelling of Inventories Subject to Obsolescence
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identifierISSN: 00251909 ; E-ISSN: 15265501
subjectEconomics -- Microeconomics -- Economic costs and benefits ; Business -- Accountancy -- Financial accounting ; Philosophy -- Epistemology -- Knowledge ; Economics -- Microeconomics -- Economic costs and benefits ; Mathematics -- Applied mathematics -- Statistics ; Mathematics -- Pure mathematics -- Probability theory ; Business -- Business economics -- Commercial production ; Mathematics -- Pure mathematics -- Probability theory ; Mathematics -- Applied mathematics -- Statistics ; Social sciences -- Population studies -- Mortality
descriptionA class of models for optimizing inventory costs is presented which takes account of stochastic obsolescence of an inventory item. Obsolescence is defined as a demand state, in such a fashion as to permit appraisal, ex ante, of the probability of arrival of obsolescence at future times, under the assumption that there are many possible states of demand. Response to obsolescence is introduced by means of a Bayesian procedure. In the most complete model this is done by modification of the state probability vector of a Markov process. Optimization is accomplished by means of a dynamic program.
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abstractA class of models for optimizing inventory costs is presented which takes account of stochastic obsolescence of an inventory item. Obsolescence is defined as a demand state, in such a fashion as to permit appraisal, ex ante, of the probability of arrival of obsolescence at future times, under the assumption that there are many possible states of demand. Response to obsolescence is introduced by means of a Bayesian procedure. In the most complete model this is done by modification of the state probability vector of a Markov process. Optimization is accomplished by means of a dynamic program.
pubInstitute of Management Sciences
date1964-09-01