Research Article
An Improved Exhausted-Food-Sources-Identification Mechanism for the Artificial Bee Colony Algorithm
@INPROCEEDINGS{10.1007/978-3-030-32216-8_62, author={Jiaxu Ning and Haitong Zhao and Peng Sun and Yunfei Feng and Tianyu Zhao}, title={An Improved Exhausted-Food-Sources-Identification Mechanism for the Artificial Bee Colony Algorithm}, proceedings={Simulation Tools and Techniques. 11th International Conference, SIMUtools 2019, Chengdu, China, July 8--10, 2019, Proceedings}, proceedings_a={SIMUTOOLS}, year={2019}, month={10}, keywords={Swarm intelligence Optimization problem Artificial Bee Colony Algorithm}, doi={10.1007/978-3-030-32216-8_62} }- Jiaxu Ning
Haitong Zhao
Peng Sun
Yunfei Feng
Tianyu Zhao
Year: 2019
An Improved Exhausted-Food-Sources-Identification Mechanism for the Artificial Bee Colony Algorithm
SIMUTOOLS
Springer
DOI: 10.1007/978-3-030-32216-8_62
Abstract
Artificial bee colony (ABC) algorithm has been widely used to solve the optimization problems. In the existing ABC algorithms, choosing which employed bee giving up its food source only based on its current trial number. It may cause some promising areas are exploited insufficiently and some non-significant areas are searched excessively. Thus, much more searching resources are wasted. To cope with this problem, an improved exhausted food source identification mechanism based on space partitioning (ISP) is designed, which considers the food source states both in the objective space and searching space simultaneously. Then, the proposed mechanism is applied to the basic ABC algorithm and a recently improved ABC algorithm. The experimental results have demonstrated that the ABC algorithms with the designed exhausted food source identification mechanism perform better than the original ABC algorithms in almost all the functions on the CEC2015 test suit.