计算机与现代化Issue(8)：9-16,8.DOI:10.3969/j.issn.1006-2475.2026.08.002
改进细菌觅食优化算法的无人机路径规划
UAV Path Planning Using an Improved Bacterial Foraging Optimization Algorithm
摘要
Abstract
Aiming at the problems of easily falling into local optimum and low solving efficiency in the complex environment of current UAV path planning,this paper proposes an Improved Bacterial Foraging Optimization(IBFO)algorithm.Firstly,a single-layer loop structure is used to replace the three-layer nested loop structure of the traditional Bacterial Foraging Optimiza-tion(BFO)algorithm,and a multimodal termination rule is designed to greatly improve the convergence speed and stability of the algorithm.Secondly,chaotic variables are introduced in the initialization phase of the BFO algorithm,so that the population can cover more solution space regions and avoid falling into local optimality.Finally,a particle swarm optimization strategy with an enhanced inter-individual communication mechanism and adaptive parameter design is introduced to dynamically adjust the search range and swimming step size of the bacteria according to the environmental concentration at the current location,so as to balance the global and local search capabilities of the algorithm and improve the local search accuracy.The results show that com-pared with the tent multi-strategy improved osprey optimization algorithm(TOOA),the average running time is reduced by 41.4%and the average planning path length is reduced by 19.5%.The experimental results show that the proposed improved bac-terial foraging optimization algorithm has obvious advantages in convergence speed,accuracy and stability,and can effectively deal with complex path planning problems.关键词
无人机/细菌觅食优化算法/单层循环结构/混沌变量/粒子群优化算法Key words
UAV/bacterial foraging optimization algorithm/single-layer loop structure/chaotic variables/particle swarm opti-mization algorithm分类
信息技术与安全科学引用本文复制引用
白俊卿,郭琳珠,耿琦鑫..改进细菌觅食优化算法的无人机路径规划[J].计算机与现代化,2026,(8):9-16,8.基金项目
西安市科技计划高校院所人才服务企业项目(23GXFW0077) （23GXFW0077）
