Authors: Kratica, Jozef 
Kojić, Jelena
Tošić, Dušan
Filipović, Vladimir
Dugošija, Đorđe
Title: Two hybrid genetic algorithms for solving the super-peer selection problem
Journal: Applications of Soft Computing
Series/Report no.: Advances in Intelligent and Soft Computing
Volume: 58
First page: 337
Last page: 346
Issue Date: 1-Jan-2009
ISBN: 978-3-540-89619-7
ISSN: 1867-5662
DOI: 10.1007/978-3-540-89619-7_33
Abstract: 
The problem that we will address here is the Super-Peer Selection Problem (SPSP). Two hybrid genetic algorithm (HGA) approaches are proposed for solving this NP-hard problem. The new encoding schemes are implemented with appropriate objective functions. Both approaches keep the feasibility of individuals by using specific representation and modified genetic operators. The numerical experiments were carried out on the standard data set known from the literature. The results of this test show that in 6 out of 12 cases HGAs outreached best known solutions so far, and that our methods are competitive with other heuristics.
Publisher: Springer Link

Show full item record

SCOPUSTM   
Citations

4
checked on May 18, 2024

Page view(s)

56
checked on May 9, 2024

Google ScholarTM

Check

Altmetric

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.