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 :
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