By Topic

A parallel local-search algorithm for the k-partitioning 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
$31 $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

4 Author(s)
Diekmann, R. ; Dept. of Math. & Comput. Sci., Paderborn Univ., Germany ; Luling, R. ; Monien, B. ; Spraner, C.

Presents a new algorithm for the k-partitioning problem which achieves an improved solution quality compared to known heuristics. We apply the principle of so-called “helpful sets”, which has been shown to be very efficient for graph bisection, to the direct k-partitioning problem. The principle is extended in several ways. We introduce a new abstraction technique which shrinks the graph during runtime in a dynamic way, leading to shorter computation times and improved solution qualities. The use of stochastic methods provides further improvements in terms of solution quality. Additionally, we present a parallel implementation of the new heuristic. The parallel algorithm delivers the same solution quality as the sequential one, while providing reasonable parallel efficiency on moderately sized MIMD systems. All results are verified by experiments for various graphs and processor numbers

Published in:

System Sciences, 1995. Proceedings of the Twenty-Eighth Hawaii International Conference on  (Volume:2 )

Date of Conference:

3-6 Jan 1995