On the Analysis of Performance of the Improved Artificial-Bee-Colony Algorithm

Authors:
Haiyan Quan;Xinling Shi
Affiliations:
-;-
Venue:
ICNC '08 Proceedings of the 2008 Fourth International Conference on Natural Computation - Volume 07
Year:
2008

Citing 0
Cited 5

A survey: algorithms simulating bee swarm intelligence

Artificial Intelligence Review
A modified Artificial Bee Colony algorithm for real-parameter optimization

Information Sciences: an International Journal
Enhancing different phases of artificial bee colony for continuous global optimisation problems

International Journal of Advanced Intelligence Paradigms
Performance analysis of the coarse-grained parallel model of the artificial bee colony algorithm

Information Sciences: an International Journal
Synergizing fitness learning with proximity-based food source selection in artificial bee colony algorithm for numerical optimization

Applied Soft Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

this paper introduces an improved artificial colony algorithm. In the algorithm, a new search iteration operator based on the fixed point theorem of Contractive Mapping in Banach Spaces is proposed. In this work, the improved artificial colony algorithm is used to 10 multivariable benchmark functions. The simulation results show that the algorithm possesses an excellent performance in the global optimization, and can be efficiently employed to solve the multimodal engineering problems with high dimensionality.