Please use this identifier to cite or link to this item: https://research.matf.bg.ac.rs/handle/123456789/678
Title: Two hybrid genetic algorithms for solving the super-peer selection problem
Authors: Kratica, Jozef
Kojić, Jelena
Tošić, Dušan
Filipović, Vladimir 
Dugošija, Djordje
Affiliations: Informatics and Computer Science 
Issue Date: 1-Jan-2009
Related Publication(s): Applications of Soft Computing, World Soft Computing (WSC) Conference 2008
Journal: Advances in Intelligent and Soft Computing
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. © Springer-Verlag Berlin Heidelberg 2009.
URI: https://research.matf.bg.ac.rs/handle/123456789/678
ISBN: 9783540896180
ISSN: 18675662
DOI: 10.1007/978-3-540-89619-7_33
Appears in Collections:Research outputs

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