Comparison of Artificial Neural Networks with a Conventional Heuristic Technique for Optimization Problems

Author

Jeffrey S. Gruner

Date of Award

12-1992

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Electrical and Computer Engineering

First Advisor

Steven K. Rogers, PhD

Abstract

This research investigates the utility of the Hopfield and Kohonen artificial neural networks to the traveling salesman optimization problem. A third, non-neural-network technique (the Christofides Algorithm - a competitive, bounded-solution operations research technique) is also investigated for comparison to the artificial neural network solutions. An eight and forty-two city distribution are chosen for comparison of the solutions.

AFIT Designator

AFIT-GSO-ENG-92D-01

DTIC Accession Number

ADA259207

Comments

The author's Vita page is omitted.

Recommended Citation

Gruner, Jeffrey S., "Comparison of Artificial Neural Networks with a Conventional Heuristic Technique for Optimization Problems" (1992). Theses and Dissertations. 7228.
https://scholar.afit.edu/etd/7228