Efficient Heuristic Algorithms for Positive 0-1 Polynomial Programming Problems.

Abstract

Two types of heuristic methods for solving polynomial programming (PP) problems were developed. The various algorithms were tested on randomly generated problems of up to 1000 variables and 200 constraints. Their performance in terms of computational time and effectiveness was investigated. The results were extremely encouraging. Optimal solutions were consistently obtained by some of the heuristic methods in over 50% of the problems solved. The effectiveness was on the average better than 99% and no less than 96.5%. The computational time using the heuristic for PP problems is on the average 5% of the time required to solve the problems to optimality.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1978
Accession Number
ADA061509

Entities

People

  • Frieda Granot

Organizations

  • Stanford University

Tags

Communities of Interest

  • Counter IED
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Coefficients
  • Computations
  • Computer Programming
  • Contracts
  • Coverings
  • Heuristic Methods
  • Integer Programming
  • Linear Programming
  • Linearity
  • Military Research
  • Operations Research
  • Polynomials
  • United States
  • United States Government

Readers

  • Neural Network Machine Learning.
  • Regression Analysis.