Skip to main content
padlock icon - secure page this page is secure

A Comparative Study of Neural Networks Methods and the African Buffalo Optimization for the Travelling Salesman’s Problems

Buy Article:

$106.51 + tax (Refund Policy)

This paper presents a comparative study of some Neural Networks methods and the newly-designed African Buffalo Optimization in solving 12 popular benchmark symmetric Travelling Salesman’s Problems. Recently, researchers are exploring solutions to difficult combinatorial problems using the Neural Networks methods. So far, the experiments have been successful. On the other hand, the metaheuristic, African Buffalo Optimization has proven to be quite effective and efficient in providing solutions to some NP-hard and NP-Complete problems, including, of course, the Travelling Salesman’s Problems. After a number of experimental evaluations on the chosen dataset, the African Buffalo Optimization was found to be more successful in solving the symmetric Travelling Salesman’s Problems under consideration.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Keywords: African Buffalo Optimization; Neural Networks; Travelling Salesman’s Problem

Document Type: Research Article

Affiliations: Faculty of Computer Systems and Software Engineering, Universiti Malaysia Pahang, Kuantan 26300, Malaysia

Publication date: November 1, 2017

More about this publication?
  • ADVANCED SCIENCE LETTERS is an international peer-reviewed journal with a very wide-ranging coverage, consolidates research activities in all areas of (1) Physical Sciences, (2) Biological Sciences, (3) Mathematical Sciences, (4) Engineering, (5) Computer and Information Sciences, and (6) Geosciences to publish original short communications, full research papers and timely brief (mini) reviews with authors photo and biography encompassing the basic and applied research and current developments in educational aspects of these scientific areas.
  • Editorial Board
  • Information for Authors
  • Subscribe to this Title
  • Ingenta Connect is not responsible for the content or availability of external websites
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more