Methods of solution of linear programs under uncertainty.
ResearchPublished 1960
A discussion of the uncertainty in most linear-programming problems, an uncertainty that is found in either the technology matrix, the right-hand side, or the cost. Some of the more usual methods of reducing the effects of uncertainty are those of (1) replacing the random elements by their expected values, (2) replacing the random elements by pessimistic estimates of their values, and (3) recasting the problem into a two-stage problem in which, in the second stage, the "inaccuracies" can be compensated for in the first-stage activities. These methods are called the expected-value solution, the "fat" solution, and the "slack" solution, respectively. This paper examines the one-stage linear program under uncertainty, indicating the relation between these various "solutions."
Document Details
- Copyright: RAND Corporation
- Availability: Available
- Year: 1960
- Print Format: Paperback
- Paperback Pages: 15
- Paperback Price: $15.00
- Document Number: P-2132
Citation
RAND Style Manual
Chicago Manual of Style
Madansky, Albert, Methods of solution of linear programs under uncertainty. RAND Corporation, P-2132, 1960. As of September 13, 2024: https://www.rand.org/pubs/papers/P2132.html
Madansky, Albert, Methods of solution of linear programs under uncertainty. Santa Monica, CA: RAND Corporation, 1960. https://www.rand.org/pubs/papers/P2132.html. Also available in print form.
This publication is part of the RAND paper series. The paper series was a product of RAND from 1948 to 2003 that captured speeches, memorials, and derivative research, usually prepared on authors' own time and meant to be the scholarly or scientific contribution of individual authors to their professional fields. Papers were less formal than reports and did not require rigorous peer review.
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.