A Novel Numerical Integration Method Based on Artificial Bee Colony Algorithm

Author

Juan Xie ; Jianfeng Qiu

Author_Institution

Dept. of Mathmatics & Phys., Anhui Univ. of Archit., Hefei, China

fYear

2012

fDate

7-9 Dec. 2012

Firstpage

531

Lastpage

534

Abstract

An new swarm intelligence algorithm based on the behavior of honeybee swarms has been proposed for some years, namely, Artificial Bee Colony(ABC). In this work, ABC is used for optimizing a set of split in a given integration interval by simulating the foraging activities of bees and reflecting the changing trends of the integrand. At the same time, this work also compares the performance of ABC algorithm with that of Trapezoidal, Simpson, Differential Evolution(DE), particle swarm optimization(PSO) for numerical integration. The simulation results show that the mentioned algorithm for numerical integration outperforms the other algorithm.

Keywords

ant colony optimisation; integration; particle swarm optimisation; ABC algorithm; PSO; Simpson evolution; artificial bee colony algorithm; differential evolution; honeybee swarm behavior; integration interval; numerical integration method; particle swarm optimization; swarm intelligence algorithm; trapezoidal evolution; Algorithm design and analysis; Approximation algorithms; Educational institutions; Optimization; Particle swarm optimization; Tin; Vectors; Artificial Bee Colony; fitness value; inequality point segmentation; numerical integration;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Engineering and Communication Technology (ICCECT), 2012 International Conference on

Conference_Location

Liaoning

Print_ISBN

978-1-4673-4499-9

Type

conf

DOI

10.1109/ICCECT.2012.118

Filename

6414049