Estimation of Fractiles for Order Point Determination.

Abstract

Inventory stocking problems with stochastic demand typically involve an estimate of the location of some fractile of the demand distribution, where the fractile is usually in the 0.8 - .99 range. This fractile is termed the 'service level' and is the probability that demands will be satisfied from stock on hand. The conventional approach of using the Normal model to estimate this location can sometimes be misleading since it uses information about the center of the distribution to predict behavior in the tail of the distribution. A new method based on a mixture model is proposed for directly estimating the location of the appropriate fractile. A formal Bayesian approach is presented and heuristic smoothing methods are developed. The statistics to be collected can be interpreted as the proportion of backorders and the average quantity backordered in each period. The estimate obtained is biased in general but robust in the sense that it works well for a variety of distributions. The performance of this method is superior to the conventional approach with some qualifications.

Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1975
Accession Number
ADA015684

Entities

People

  • Uday S. Karmarkar

Organizations

  • Massachusetts Institute of Technology

Tags

DTIC Thesaurus Topics

  • Bayesian Networks
  • Computing-Related Activities
  • Data Science
  • Information Science
  • Interdisciplinary Science
  • Inventory
  • Mathematics
  • Models
  • Probability
  • Qualifications
  • Statistical Analysis
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Logistics and Supply Chain Management.
  • Regression Analysis.
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference