Linear Decision Models Under Risk.

Abstract

The assumption made in linear programming that the components are Deterministic (constant) numbers is rarely fulfilled in practical applications. This has led to the development of the field of stochastic programming where the random aspect of the coefficients in the objective function, technology matrix, and the vector of resources are taken into account. This research investigates the problem of a linear program with uncertainty attached to the decision vector. For example, a decision to order a certain amount of a perishable good might yield variable amounts of this good at delivery due to spoilage.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1978
Accession Number
ADA059859

Entities

People

  • Terry R. Harms

Organizations

  • University of California, Berkeley

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Algorithms
  • California
  • Computer Programming
  • Convex Programming
  • Convex Sets
  • Distribution Functions
  • Linear Programming
  • Mathematical Programming
  • Measuring Instruments
  • Operations Research
  • Probability
  • Random Variables
  • Real Numbers
  • Simplex Method
  • Systems Engineering
  • Uncertainty
  • Universities

Fields of Study

  • Mathematics

Readers

  • Operations Research