An Improved Primal Simplex Variant for Pure Processing Networks.

Abstract

In processing networks, ordinary network constraints are supplemented by proportional flow restrictions on arcs entering or leaving some nodes. This paper describes a new primal partitioning algorithm for solving pure processing networks using a working basis of variable dimension. In testing against MPSX/370 on a class of randomly generated problems, a FORTRAN implementation of this algorithm was found to be an order of magnitude faster. Besides indicating the use of our methods in stand alone fashion, the computational results also demonstrate the desirability of using these methods as a high-level module in a mathematical programming system. Keywords include: Networks, Processing networks, Linear programming, and Mathematical programming systems.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1986
Accession Number
ADA176101

Entities

People

  • Chou-hong J. Chen
  • Michael D. Chang
  • Michael Engquist

Organizations

  • University of Texas at Austin

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Assembly
  • Assembly Languages
  • Computer Programming
  • Evolutionary Algorithms
  • Heuristic Methods
  • Integer Programming
  • Language
  • Linear Programming
  • Mathematical Programming
  • New York
  • Operations Research
  • Optimization
  • Procedures (Computers)
  • Simplex Method
  • Sparse Matrix
  • Standards

Fields of Study

  • Computer science

Readers

  • Operations Research
  • Systems Analysis and Design