SOLUTION PROCEDURES FOR MULTI-STAGE LINEAR PROGRAMMING UNDER UNCERTAINTY AND APPLICATIONS.

Abstract

In considering linear programming with stochastic parameters it is necessary to distinguish two types of models; first, the static model, for which only one decision has to be made and second, the dynamic models which involve sequential decision-making. A majority of the LP formulations that occur in applications are, at least in principle, sequential in nature and involve parameters that are known with certainty. One of the primary objectives of the dissertation is to define a class of what we call Dynamic Linear Programming Under Uncertainty models and to provide a theoretical framework for developing algorithms for solving such problems. (Author)

Document Details

Document Type
Technical Report
Publication Date
May 19, 1969
Accession Number
AD0693159

Entities

People

  • Rajagopalan Jagannathan

Organizations

  • Carnegie Mellon University

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Computer Programming
  • Evolutionary Algorithms
  • Heuristic Methods
  • Linear Programming
  • Mathematics
  • Simplex Method
  • Theses
  • Uncertainty

Fields of Study

  • Mathematics

Readers

  • Computational Modeling and Simulation
  • Operations Research