DocumentCode :
3757185
Title :
Efficient Exploration Strategies for Artificial Bee Colony
Author :
Chun-Ling Lin;Sheng-Ta Hsieh;Shih-Yuan Chiu
Author_Institution :
Dept. of Electr. Eng., Ming Chi Univ. of Technol. New Taipei City, Taipei, Taiwan
fYear :
2015
Firstpage :
309
Lastpage :
313
Abstract :
Artificial bee colony (ABC) is a population-based optimizer. It simulates bees´ forage behavior for searching better foods source (solutions) in solution space. In order to easier for finding better foods more efficient, in this paper, the efficient exploration strategies are proposed. Unlike original ABC, the scout bee will only be activated for a while. For proposed method, the scout bee will be joined in each iteration. In order to test the efficiency of proposed method, twenty-five test functions of CEC 2005 are adopted to compare the proposed method with four ABC variants. From the results, it can be observed that the proposed method performs better on most test functions.
Keywords :
"Information management","Optimization","Mathematical model","Genetic algorithms","Flowcharts","Convergence","Gaussian distribution"
Publisher :
ieee
Conference_Titel :
Computing and Networking (CANDAR), 2015 Third International Symposium on
Electronic_ISBN :
2379-1896
Type :
conf
DOI :
10.1109/CANDAR.2015.83
Filename :
7424731
Link To Document :
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