Associate professor
Supervisor of Master's Candidates
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Affiliation of Author(s):计算机科学与工程学院
Journal:2020 International Conference on Data Processing Algorithms and Models, ICDPAM 2020
Funded by:自选课题
Abstract:In this paper, we propose an enhancement algorithm of colliding bodies optimization based on rotation learning, named by RBL-CBO. Firstly, we use the rotation-based learning to search for any point in the rotating space by adjusting the rotation angle, thereby improving the ability of the proposed algorithm jump out of the local optimum. Next, we leverage the sinusoid-based nonlinear adjustment strategy to modify the control parameters to improve the calculation accuracy of the proposed algorithm. Finally, we process the cross-boundary object by the mirroring strategy. We conduct extensive experiments to test the performance of the proposed algorithm. In simulation-based experiments, 23 benchmark functions are used to compare RBL-CBO algorithm with the CBO, DE, BBO, PSO and GSA algorithm. The experimental results demonstrate that the proposed RBL-CBO algorithm is superior to the other comparison algorithms, while the RBL-CBO algorithm is at least 20% higher than the CBO algorithm in terms of the accuracy of solving function optimization problem.
Co-author:刘慧,liyong,崔世琦
First Author:Kevin Liu
Indexed by:Journal paper
Volume:1774
Page Number:2
ISSN No.:1742-6588
Translation or Not:no
Date of Publication:2021-02-03
