Current position: Home >> Scientific Research >> Paper Publications

Artificial bee colony algorithm and pattern search hybridized for global optimization

Release Time:2019-03-09  Hits:

Indexed by: Journal Article

Date of Publication: 2013-04-01

Journal: APPLIED SOFT COMPUTING

Included Journals: EI、SCIE

Volume: 13

Issue: 4

Page Number: 1781-1791

ISSN: 1568-4946

Key Words: Artificial bee colony algorithm; Swarm intelligence; Memetic algorithm; Evolutionary computation; Global optimization

Abstract: Artificial bee colony algorithm is one of the most recently proposed swarm intelligence based optimization algorithm. A memetic algorithm which combines Hooke-Jeeves pattern search with artificial bee colony algorithm is proposed for numerical global optimization. There are two alternative phases of the proposed algorithm: the exploration phase realized by artificial bee colony algorithm and the exploitation phase completed by pattern search. The proposed algorithm was tested on a comprehensive set of benchmark functions, encompassing a wide range of dimensionality. Results show that the new algorithm is promising in terms of convergence speed, solution accuracy and success rate. The performance of artificial bee colony algorithm is much improved by introducing a pattern search method, especially in handling functions having narrow curving valley, functions with high eccentric ellipse and some complex multimodal functions. (C) 2013 Elsevier B. V. All rights reserved.

Prev One:Artificial neural network model for evaluating gravelly soils liquefaction using shear wave velocity

Next One:Application of the artificial bee colony algorithm-based projection pursuit method in statistical rock mass stability estimation