A Demyanov-Type Modification for Generalized Linear Programming.

Abstract

The properties were studied of the direction formed by taking the difference of two successive dual iterates of generalized linear programming (GLP), and pointed out that this direction is also solution to an associated direction finding problem. This study shows that this direction finding problem belongs to a new class of direction finding problems and propose a modification of GLP in which its original direction finding problems is replaced by another in this new class. This new direction finding problem is similar to the one used by Demyanov for minimax problems and guarantees an ascent direction for the dual function. Finally, we state and prove the convergence for the modified GLP. Keywords: Linear programming; Decomposition; Lagrangian dual; Subgradient.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1987
Accession Number
ADA188959

Entities

People

  • Donald W. Hearn
  • Siriphong Lawphongpanich

Organizations

  • University of Florida

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Classification
  • Computer Programming
  • Convergence
  • Direction Finding
  • Guarantees
  • Industrial Engineering
  • Inequalities
  • Linear Programming
  • Mathematical Programming
  • Mathematics
  • Military Research
  • New York
  • Nonlinear Programming
  • Operations Research
  • Optimization
  • Systems Engineering

Fields of Study

  • Mathematics

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  • Operations Research