A hybrid random-key genetic algorithm for a symmetric travelling salesman problem
by Funda Samanlioglu, Mary Beth Kurz, William G. Ferrell, Sarat Tangudu
International Journal of Operational Research (IJOR), Vol. 2, No. 1, 2007

Abstract: This paper describes a methodology that finds approximate and sometimes optimal solutions to the symmetric Travelling Salesman Problem (TSP) using a hybrid approach that combines a Random-Key Genetic Algorithm (RKGA) with a local search procedure. The random keys representation ensures that feasible tours are constructed during the application of genetic operators, whereas the genetic algorithm approach with local search efficiently generates optimal or near-optimal solutions. The results of experiments are provided that use examples taken from a well-known online library to confirm the quality of the proposed algorithm.

Online publication date: Thu, 30-Nov-2006

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Operational Research (IJOR):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com