Title :
An Improved Artificial Bee Colony Algorithm
Author :
Kang, Fei ; Li, Junjie ; Li, Haojin ; Ma, Zhenyue ; Xu, Qing
Author_Institution :
Fac. of Infrastruct. Eng., Dalian Univ. of Technol., Dalian, China
Abstract :
Artificial bee colony (ABC) algorithm is one of the most recently proposed swarm intelligence algorithms for global optimization. It performs well in most cases; however, there still exist some problems it cannot solve very well. This paper presents a novel hybrid Hooke Jeeves ABC (HJABC) algorithm with intensification search based on the Hooke Jeeves pattern search and the ABC. The main purpose is to demonstrate how the standard ABC can be improved by incorporating a hybridization strategy. The proposed algorithm is tested on 7 benchmark functions including a wide range of dimensions. Numerical results show that the new algorithm is promising in terms of convergence speed, success rate and solution accuracy.
Keywords :
optimisation; search problems; Hooke Jeeves ABC algorithm; Hooke Jeeves pattern search; benchmark functions; global optimization; improved artificial bee colony algorithm; swarm intelligence algorithms; Artificial intelligence; Benchmark testing; Convergence of numerical methods; Particle swarm optimization; Performance analysis;
Conference_Titel :
Intelligent Systems and Applications (ISA), 2010 2nd International Workshop on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5872-1
Electronic_ISBN :
978-1-4244-5874-5
DOI :
10.1109/IWISA.2010.5473452