中南民族大学学报（自然科学版）2026，Vol.45Issue(4)：540-547,8.DOI:10.20056/j.cnki.ZNMDZK.20250853
融合多策略的蜣螂算法的三维无人机航迹规划
Three-dimensional UAV path planning based on Dung Beetle Algorithm fused with multiple strategies
摘要
Abstract
To address the deficiencies of the Dung Beetle Optimizer(DBO)in UAV path planning-namely,insufficient population diversity,slow convergence,and weak global exploration,a multi-strategy-enhanced variant termed BDBO is proposed.The algorithm seamlessly integrates four synergistic components throughout the entire planning process:dynamic-learning-based good-point set initialization,time-triggered active parallel bilateral search,a natural population-decay mechanism,and a boundary convergence strategy fused with a Sigmoid function.Collectively,these strategies rapidly expand the feasible flight-corridor during the global phase and refine waypoint positions in the local phase,thereby accelerating convergence and improving solution accuracy simultaneously.A composite objective function aggregating path length,flight safety,trajectory smoothness,and altitude cost is minimized on both CEC2017 benchmarks and a realistic 3-D mountainous scenario.Experimental results reveal that BDBO reduces the best fitness value by 19.47％,25.51％,20.85％,and 3.97％compared with four state-of-the-art counterparts,unequivocally demonstrating its effectiveness and superiority for three-dimensional UAV path planning.关键词
蜣螂算法/主动并行双边搜索/自然衰减种群优化法/选择边界收敛策略Key words
Dung Beetle algorithm/active parallel bilateral search/natural decay population optimization/selected boundary convergence strategy分类
信息技术与安全科学引用本文复制引用
李尧,黄大庆,徐文校,赵喆..融合多策略的蜣螂算法的三维无人机航迹规划[J].中南民族大学学报（自然科学版）,2026,45(4):540-547,8.基金项目
中国高校产学研创新基金资助项目(2021ZYA04004) （2021ZYA04004）
