A Comparison of Maximum Likelihood Exponential Smoothing and Bayes Forecasting Procedures in Inventory Modeling

Abstract

The paper compares four major schemes used for forecasting mean demand to be used as input into an inventory model so that optimum stockage levels can be obtained. The inventory model is the classical order up to S , infinite horizon model with carry-over from period to period and complete backordering. Maximum likelihood, exponential smoothing, standard Bayes and adaptive Bayes schemes are used and results, via Monte Carlo simulation, are obtained for the total sum of discounted costs for stationary demand, long term trend and shock changes in mean demand.

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Document Details

Document Type
Technical Report
Publication Date
Apr 19, 1972
Accession Number
AD0742340

Entities

People

  • Donald Gross
  • Robert J. Craig

Organizations

  • George Washington University

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Communities of Interest

  • Air Platforms
  • Materials and Manufacturing Processes

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Fields of Study

  • Mathematics

Readers

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