AURA User's Manual

Vol. II, Data Input and Sample Problem

Robert Shishko, Milton Kamins, Donald E. Emerson

ResearchPublished 1983

AURA (Army Unit Readiness/Sustainability Assessor) is a Monte Carlo discrete-event simulation model intended for analyzing the interrelations among the resources associated with a set of combat units, and the capability of those units to generate combat missions in a dynamic, rapidly evolving wartime environment. This volume is the second of two being prepared as a User's Manual for AURA. It discusses the input requirements, procedures, and formats, and provides a sample problem based on a hypothetical Army combat vehicle. These detailed discussions provide the only complete explanations for some of the numerous control options available with AURA and must be considered mandatory reading for potential AURA users. The sample problem illustrates an AURA database and the various outputs available with AURA. Volume I of this series describes the capabilities and processing logic of the model.

Order a Print Copy

Format
Paperback
Page count
152 pages
List Price
$35.00
Buy link
Add to Cart

Document Details

  • Availability: Available
  • Year: 1983
  • Print Format: Paperback
  • Paperback Pages: 152
  • Paperback Price: $35.00
  • Document Number: N-1988-MRAL

Citation

RAND Style Manual
Shishko, Robert, Milton Kamins, and Donald E. Emerson, AURA User's Manual: Vol. II, Data Input and Sample Problem, RAND Corporation, N-1988-MRAL, 1983. As of September 12, 2024: https://www.rand.org/pubs/notes/N1988.html
Chicago Manual of Style
Shishko, Robert, Milton Kamins, and Donald E. Emerson, AURA User's Manual: Vol. II, Data Input and Sample Problem. Santa Monica, CA: RAND Corporation, 1983. https://www.rand.org/pubs/notes/N1988.html. Also available in print form.
BibTeX RIS

This publication is part of the RAND note series. The note was a product of RAND from 1979 to 1993 that reported miscellaneous outputs of sponsored research for general distribution.

This document and trademark(s) contained herein are protected by law. This representation of RAND intellectual property is provided for noncommercial use only. Unauthorized posting of this publication online is prohibited; linking directly to this product page is encouraged. Permission is required from RAND to reproduce, or reuse in another form, any of its research documents for commercial purposes. For information on reprint and reuse permissions, please visit www.rand.org/pubs/permissions.

RAND is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.