RISK AVERSION IN STOCHASTIC PROGRAMMING WITH RECOURSE.

Abstract

In stochastic programming with recourse the objective is to maximize expected net payoff. This implicitly assumes no aversion to risk. This paper introduces risk aversion into stochastic programming with recourse. The objective becomes to maximize the expected (concave) utility of the net payoffs. Because of the special structure of the problem a number of computational short cuts are possible in the mathematical program that results. The latest representation of the gradient is but a slight modification of the latest representation of the linear objective function without risk aversion. All the second stage problems can be solved as linear programs. Unfortunately it appears necessary to solve the first stage problem as a non-linear program. (Author)

Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1968
Accession Number
AD0667968

Entities

People

  • David Rutenberg

Organizations

  • Carnegie Mellon University

Tags

DTIC Thesaurus Topics

  • Applied Mathematics
  • Computer Programming
  • Computing-Related Activities
  • Convex Programming
  • Interdisciplinary Science
  • Linear Programming
  • Mathematical Programming
  • Mathematics

Fields of Study

  • Computer science

Readers

  • Calculus or Mathematical Analysis
  • Computational Modeling and Simulation
  • Neuroscience