The Complementary Unboundedness of Dual Feasible Solution Sets in Convex Programming,

Abstract

F. E. Clark has shown that if at least one of the feasible solution sets for a pair of dual linear programming problems is nonempty then at least one of them is both nonempty and unbounded. Subsequently, M. Avriel and A. C. Williams have obtained the same result in the more general context of (prototype posynomial) geometric programming. In this paper it is shown that the same result is actually false in the even more general context of convex programming - unless a certain regularity condition is satisfied. It is also shown that the regularity condition is so weak that it is automatically satisfied in linear programming, (prototype posynomial) geometric programming, quadratic programming (with either linear or quadratic constraints), l sub p -regression analysis, optimal location, roadway network analysis, and chemical equilibrium analysis. Moreover, the author develops an equivalent regularity condition for each of the usual formulations of duality.

Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1975
Accession Number
ADA019584

Entities

People

  • Elmor L. Peterson

Organizations

  • Northwestern University

Tags

DTIC Thesaurus Topics

  • Applied Mathematics
  • Chemical Equilibrium
  • Computer Programming
  • Convex Programming
  • Geometric Programming
  • Interdisciplinary Science
  • Linear Programming
  • Mathematical Programming
  • Mathematics
  • Operations Research
  • Prototypes
  • Quadratic Programming
  • Regression Analysis
  • Systems Science

Fields of Study

  • Mathematics

Readers

  • Linear Algebra
  • Mathematical Modeling and Probability Theory.