Improved Artificial Bee Colony Algorithm Based on Cauchy OBL

• Published in: Journal of physics. Conference series Vol. 1920; no. 1; pp. 12108 - 12115
• Main Authors: Ren, Zuochen, Zhang, Liyi, Tang, Jinyan, Liu, Ting
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.05.2021
• Subjects: Convergence; Local optimization; Optimization algorithms; Physics; Search algorithms; Swarm intelligence
• ISSN: 1742-6588; 1742-6596
• DOI: 10.1088/1742-6596/1920/1/012108

Abstract Artificial bee colony algorithm is a competitive swarm optimization algorithm for many optimization problems. However, traditional artificial bee colony algorithms often have the problems of insufficient development performance, easy to fall into local optimization and slow convergence. In order to overcome this defect, this paper introduces Cauchy OBL into artificial bee colony algorithm, and proposes an artificial bee colony algorithm based on Cauchy OBL. In the initialization stage, the algorithm uses the Cauchy OBL group to compete with the traditional initial group, selects excellent individuals to form an improved initial group, and improves the quality and diversity of the population; in the neighborhood search stage, the Cauchy OBL process is added to improve the global exploration ability of the algorithm. At the same time, in order to speed up the convergence speed, the global optimal solution and multi-dimensional update strategy are introduced. The simulation results show that the improved algorithm is easy to jump out of the local optimization and has higher search accuracy and faster convergence speed.