MATHEMATICAL PROGRAMMING AND OPTIMAL CONTROL THEORY

Abstract

Let K be a closed convex set in E superscript (m + 1) and L = (P = (P sub 0, ..., P sub m): P sub 1 = P sub 2 = ...P sub m = 0). Then for the simple problem: Minimize P sub 0 Subject to P = (P sub 0, P sub 1, ..., P sub m) epsilon the intersection of K and L, we prove a duality theorem and the convergence of a solution algorithm modeled on the duality theorem and the simplex method of linear programming respectively. Specialization of this general model to linear programming, convex programming, generalized programming, control theory, and the decomposition approach to mathematical programming yield the appropriate duality theorems and solution algorithms in each case.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1968
Accession Number
AD0682580

Entities

People

  • Richard M. Van Slyke

Organizations

  • University of California, Berkeley

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Algorithms
  • Computational Science
  • Computer Programming
  • Control Theory
  • Convex Programming
  • Convex Sets
  • Differential Equations
  • Equations
  • Evolutionary Algorithms
  • Linear Programming
  • Mathematical Programming
  • Operations Research
  • Optimization
  • Real Variables
  • Simplex Method
  • Systems Engineering
  • Theorems

Fields of Study

  • Mathematics

Readers

  • Linear Algebra
  • Operations Research

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms