DocumentCode
234726
Title
Adaptive Central Force Optimization with Variable Population Size
Author
Liu Jie
Author_Institution
Coll. of Math. & Stat., Xi´dian Univ., Xi´an, China
fYear
2014
fDate
15-16 Nov. 2014
Firstpage
17
Lastpage
20
Abstract
A improving central force optimization algorithm (CFO) is proposed in this paper. New algorithm can adjust the size of population dynamically. With population evolution, algorithm balance the exploration and exploitation effectively. Experiments on 4 test functions show that the new algorithm is able to find good optimal solutions efficiently. Compared with existing algorithms, new algorithm improves solution accuracy with less computational effort.
Keywords
optimisation; CFO; adaptive central force optimization; population evolution; variable population size; Algorithm design and analysis; Force; Heuristic algorithms; Optimization; Probes; Sociology; Statistics; central force optimization; global optimization; population size;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Security (CIS), 2014 Tenth International Conference on
Conference_Location
Kunming
Print_ISBN
978-1-4799-7433-7
Type
conf
DOI
10.1109/CIS.2014.46
Filename
7016844
Link To Document