Resolving Degeneracy in Combinatorial Linear Programs: Steepest Edge, Steepest Ascent, and Closest Ascent

Abstract

While variants of the steepest edge pivoting rule are commonly used in linear programming codes they are not known to have the theoretically attractive property of avoiding an infinite sequence of pivots at points of degeneracy. A natural extension of the steepest edge pivoting rule based on steepest ascent is developed and shown to be provably finite. An alternative finite pivoting procedure that is computationally more attractive than steepest ascent is then introduced and it is argued that with probability 1 the procedure has the same computational requirements as steepest edge independent of the linear program being solved. Both procedures have the unique advantage that they choose the pivot element without explicit knowledge of the set of all active constraints at a point of degeneracy, thus making them attractive in combinatorial settings where the linear program is never explicitly written out.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1991
Accession Number
ADA452255

Entities

People

  • E. A. Boyd

Organizations

  • Rice University

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Applied Mathematics
  • Convex Programming
  • Information Operations
  • Interdisciplinary Science
  • Linear Programming
  • Mathematical Programming
  • Mathematics
  • Operations Research
  • Probability
  • Sequences
  • Systems Science

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Linear Algebra