DESCRIPTION OF THE COMPUTER PROGRAM FOR AGGREGATE BASE STOCKAGE POLICY OF RECOVERABLE ITEMS,

Abstract

This Memorandum describes a computer program that calculates stock levels across a set of recoverable items, which are generally characterized by high unit cost and low demand. The inventory policy followed is to reorder a unit whenever one is demanded. The assumed demand distribution is stuttering Poisson. The distribution of response time is arbitrary since only the mean response time needs to be known. The technique of Bayesian inference is used for demand prediction. Some salient features of the program are: (1) It adopts an aggregate approach to stock policy. (2) It provides for setting the most efficient base stock level to satisfy a specified aggregate performance rating with the least investment, and for generating a single computer run of sets of efficient base stock levels corresponding to levels of aggregate performance. (3) For computers with small storage capacity, it reduces the problem size by categorizing items according to their past demands and cost characteristics. (4) Execution time for the program is relatively short. The operating procedure is applicable to the RAND installation of IBM 7040-7044 computers. The program /s written in FORTRAN IV (it is also available in FORTRAN II).

Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1965
Accession Number
AD0615261

Entities

People

  • Gabriele Michels
  • John Lu

Organizations

  • RAND Corporation

Tags

DTIC Thesaurus Topics

  • Bayesian Inference
  • Computer Programs
  • Computers
  • Computing Devices
  • Data Science
  • Data Storage Systems
  • Information Science
  • Inventory
  • Investments
  • Neurobehavioral Manifestations

Readers

  • Computer Science.
  • Logistics and Supply Chain Management.
  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference