METHODS OF SOLUTION OF LINEAR PROGRAMS UNDER UNCERTAINTY. NOTES ON LINEAR PROGRAMMING AND EXTENSIONS. PART 56
Abstract
Most applied linear-programming problems involve uncertainty in either the technology matrix, the requirement vector, or the cost. Some of the more usual methods of reducing the effects of uncertainty are (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 program so that, in the second stage, one can compensate for inaccuracies in the activities of the first stage. These methods are called the expected-value solution, the fat solution, and the slack solution, respectively. The one-stage linear program is examined under uncertainty in some detail, pointing out the relation between these various solutions. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Apr 06, 1961
- Accession Number
- AD0257816
Entities
People
- Albert Madansky
Organizations
- RAND Corporation