The Application of Exponential Smoothing to Forecasting Demand for Economic Order Quantity Items.

Abstract

Effective management of economic order quantitiy (EOQ) items at an Air Force base consolidated supply activity requires the use of a demand forecasting technique to routinely estimate future demand for the purpose of establishing stock levels. This study compares the effectiveness of four forecasting models feasible for use at base level. The moving averages method and three exponential smoothing models (single, double and triple) are evaluated using 22 months of demand history for a random sample of 34 EOQ items stocked at a base consolidate supply activity. Four statistical error measures are used to compare the accuracy of the forecasts generated by the models for the items. (AUthor)

Document Details

Document Type
Technical Report
Publication Date
Jan 28, 1972
Accession Number
AD0743412

Entities

People

  • Donald C. Fischer Jr.
  • Paul S. Gibson

Organizations

  • Air Force Institute of Technology

Tags

DTIC Thesaurus Topics

  • Accuracy
  • Air Force
  • Air Force Facilities
  • Collaborative Techniques
  • Data Science
  • Delphi Method
  • Errors
  • Information Science
  • Knowledge Management
  • Management Engineering
  • Statistical Samples

Readers

  • Logistics and Supply Chain Management.
  • Statistical inference.