DocumentCode
120117
Title
An Improved Cuckoo Search Algorithm with Adaptive Method
Author
Zhenxing Zhang ; Yongjie Chen
Author_Institution
Coll. of Autom., Harbin Eng. Univ., Harbin, China
fYear
2014
fDate
4-6 July 2014
Firstpage
204
Lastpage
207
Abstract
To improve the refining ability and convergence rate of cuckoo search algorithm for finding optimal solution. An improved cuckoo search algorithm with adaptive method is proposed. The self-adaptive machine is used to control the scaling factor and find probability so as to improve population diversity and avoid premature, as a result, more individuals participating in the evolution, and then refining ability and convergence rate are improved. The result of experiment show the ICS algorithm has better performance when lots of test functions are considered, ICS algorithm has faster convergence speed and higher precision.
Keywords
convergence of numerical methods; probability; search problems; ICS algorithm; adaptive method; cuckoo search algorithm; optimal solution; probability; scaling factor; self-adaptive machine; Algorithm design and analysis; Convergence; Educational institutions; Optimization; Particle swarm optimization; Refining; Standards; Cuckoo search algorithm; convergence rate; optimal solution; refining ability; self-adaptive machine;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Sciences and Optimization (CSO), 2014 Seventh International Joint Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4799-5371-4
Type
conf
DOI
10.1109/CSO.2014.45
Filename
6923669
Link To Document