Multi-Strategy Improved Secretary Bird Optimization Algorithm

作     者：Fengkai Wang Bo Wang Fengkai Wang;Bo Wang

作者机构：College of Science Shenyang University of Technology Shenyang China 

出 版 物：《Journal of Computer and Communications》 (电脑和通信(英文))

年 卷 期：2025年第13卷第1期

页      面：90-107页

学科分类：07[理学] 0701[理学-数学] 070101[理学-基础数学] 

主　　题：Secretary Bird Optimization Algorithm Iterative Mapping Adaptive Weight Strategy Cauchy Variation Convergence Speed 

摘      要：This paper addresses the shortcomings of the Sparrow and Eagle Optimization Algorithm (SBOA) in terms of convergence accuracy, convergence speed, and susceptibility to local optima. To this end, an improved Sparrow and Eagle Optimization Algorithm (HS-SBOA) is proposed. Initially, the algorithm employs Iterative Mapping to generate an initial sparrow and eagle population, enhancing the diversity of the population during the global search phase. Subsequently, an adaptive weighting strategy is introduced during the exploration phase of the algorithm to achieve a balance between exploration and exploitation. Finally, to avoid the algorithm falling into local optima, a Cauchy mutation operation is applied to the current best individual. To validate the performance of the HS-SBOA algorithm, it was applied to the CEC2021 benchmark function set and three practical engineering problems, and compared with other optimization algorithms such as the Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), and Whale Optimization Algorithm (WOA) to test the effectiveness of the improved algorithm. The simulation experimental results show that the HS-SBOA algorithm demonstrates significant advantages in terms of convergence speed and accuracy, thereby validating the effectiveness of its improved strategies.