By Topic

A learning automaton based approach to solve the graph bandwidth minimization problem

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Ali Safari Mamaghani ; Young Researchers Club, Bonab Branch, Islamic Azad University, Iran ; Mohammad Reza Meybodi

In this paper we develop a novel approximated procedure for the problem of reducing the bandwidth of a graph. This problem consists of finding a permutation of the rows and columns of a given matrix, which keeps the nonzero elements in a band that is as close as possible to the main diagonal. The new algorithm is based on object migration learning automaton. The algorithm is evaluated on a set of 113 well-known benchmark instances of the literatures and compared with several state-of-the-art algorithms, showing improvements of some previous best results. The positive point of the new proposed algorithm that it can balance the quality of results and running times. So the algorithm can lead to good results in a short running time.

Published in:

Application of Information and Communication Technologies (AICT), 2011 5th International Conference on

Date of Conference:

12-14 Oct. 2011