Constrained Optimization Using Iterated Partial Kuhn-Tucker Vectors.

Abstract

A frequently occurring problem is that of minimizing a convex function subject to a finite set of inequality constraints. Often what makes this problem difficult is the sheer number of constraints. That is, we could solve this problem for a smaller set of constraints, but solving for the total set causes difficulty. Here the authors discuss an approach which uses our ability to solve these partial problems to lead to a total solution. They illustrate the method with several examples in the last section of the paper. This approach will be somewhat heuristic in nature to promote understanding.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1984
Accession Number
ADA145476

Entities

People

  • P. C. Wollan
  • R. L. Dykstra

Organizations

  • University of Iowa

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Computer Programming
  • Computer Programs
  • Convex Programming
  • Geometry
  • Inequalities
  • Information Theory
  • Iterations
  • Mathematical Analysis
  • Military Research
  • New York
  • Optimization
  • Probability
  • Probability Distributions
  • Statistical Inference
  • Statistics

Fields of Study

  • Mathematics

Readers

  • Educational Psychology
  • Operations Research