An Adaptive Fruit Fly Optimization Algorithm for Optimization Problems
An Adaptive Fruit Fly Optimization Algorithm for Optimization Problems作者机构：College of Computers and Engineering Chongqing Three Gorges University Chongqing China College of Mathematics and Statistics Chongqing Three Gorges University Chongqing China
出 版 物：《Journal of Applied Mathematics and Physics》 (应用数学与应用物理（英文）)
年 卷 期：2023年第11卷第11期
页 面：3641-3650页
学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）]
主 题：Swarm Intelligent Optimization Algorithm Fruit Fly Optimization Algorithm Adaptive Step Local Optimum Convergence Speed
摘 要：In this paper, we present a new fruit fly optimization algorithm with the adaptive step for solving unconstrained optimization problems, which is able to avoid the slow convergence and the tendency to fall into local optimum of the standard fruit fly optimization algorithm. By using the information of the iteration number and the maximum iteration number, the proposed algorithm uses the floor function to ensure that the fruit fly swarms adopt the large step search during the olfactory search stage which improves the search speed;in the visual search stage, the small step is used to effectively avoid local optimum. Finally, using commonly used benchmark testing functions, the proposed algorithm is compared with the standard fruit fly optimization algorithm with some fixed steps. The simulation experiment results show that the proposed algorithm can quickly approach the optimal solution in the olfactory search stage and accurately search in the visual search stage, demonstrating more effective performance.
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