Modelling, Transformations, and Scaling Decisions in Constrained Optimization Problems

Abstract

This thesis investigates various modelling choices and modelling decisions that can be used by defense analysts when solving nonlinear optimization problems. A discussion is given of separable programming, goal programming, and linear fractional programming models, and a description of the manner by which they can be converted to equivalent linear programs. Transformations of variables recommended in the literature are tested on several well-known test problems using GRG and SUMT nonlinear programming codes. The sensitivity of the GRG code to scaling, rotation of coordinates, and translation of variables is examined. Transformations to obtain separability of variables and experiments using a diagonalization algorithm to transform quadratic expressions into sums of squares are discussed. Barrier and penalty function transformations are also considered.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1976
Accession Number
ADA026396

Entities

People

  • John J. Timar

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Algorithms
  • California
  • Classification
  • Computer Programming
  • Computer Programs
  • Computers
  • Convex Programming
  • Evolutionary Algorithms
  • Goal Programming
  • Linear Programming
  • Mathematical Models
  • Mathematical Programming
  • Nonlinear Programming
  • Operations Research
  • Optimization
  • Simplex Method
  • Systems Engineering

Readers

  • Calculus or Mathematical Analysis
  • Computational Modeling and Simulation
  • Operations Research