By Topic

Starting configuration of Cuckoo Search algorithm using Centroidal Voronoi Tessellations

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

2 Author(s)
Shatnawi, M. ; Comput. Sci. Dept., Univ. Kebangsaan Malaysia, Bangi, Malaysia ; Nasrudin, M.F.

Cuckoo Search (CS) is a meta-heuristic optimization algorithm that is inspired by breeding strategy of some cuckoo species that involves laying of eggs in the nests of other host birds. Like other population based optimization algorithms, the initial positions of the population, in the case of CS are host nests, will influence the performance of the searching. Based on this fact, we believe that the CS algorithm can further be improved by strategically selecting the starting positions of the nests instead of the standard random selection. This work suggests the use of positions generated from the Centroidal Voronoi Tessellations (CVT) as the starting points for the nests. A CVT is a Voronoi tessellation of a set such that the generators of the Voronoi sets are simultaneously their centers of mass. The CVT will initially present the problem space in equally distributed manner. The performance of CS algorithm initialized using CVT is compared with those generated from the standard CS algorithm on several benchmark test functions. The results show that the initialization of CS algorithm using the CVT improves its performance especially for benchmark functions with high-dimensional input spaces.

Published in:

Hybrid Intelligent Systems (HIS), 2011 11th International Conference on

Date of Conference:

5-8 Dec. 2011