基于邻域搜索策略的蜣螂优化算法及应用

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基于邻域搜索策略的蜣螂优化算法及应用

Dung Beetle Optimization Algorithm Based on Neighborhood Search Strategy and Application

基于邻域搜索策略的蜣螂优化算法及应用

Dung Beetle Optimization Algorithm Based on Neighborhood Search Strategy and Application

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doi:10.16088/j.issn.1001-6600.2024040902

广西师范大学学报（自然科学版） ›› 2025, Vol. 43 ›› Issue (2): 149-167.doi: 10.16088/j.issn.1001-6600.2024040902

杜晓昕^1,2*, 牛丽明¹, 王波^1,2, 王一萍^1,2, 李长荣^1,2, 王振飞¹

1.齐齐哈尔大学计算机与控制工程学院, 黑龙江齐齐哈尔 161006;
2.黑龙江省大数据网络安全检测分析重点实验室(齐齐哈尔大学), 黑龙江齐齐哈尔 161006

收稿日期:2024-04-09 修回日期:2024-06-26 出版日期:2025-03-05 发布日期:2025-04-02
通讯作者: 杜晓昕(1983—), 女, 江苏徐州人, 齐齐哈尔大学教授。E-mail: xiaoxindu@qqhru.edu.cn
基金资助:
国家自然科学基金面上项目(42271409); 黑龙江省自然科学基金(LH2021D022); 黑龙江省省属高等学校基本科研业务费自然科学类青年创新人才项目(145209206)

DU Xiaoxin^1,2*, NIU Liming¹, WANG Bo^1,2, WANG Yiping^1,2, LI Changrong^1,2, WANG Zhenfei¹

1. College of Computer and Control Engineering, Qiqihar University, Qiqihar Heilongjiang 161006, China;
2. Heilongjiang Key Laboratory of Big Data Network Security Detection and Analysis (Qiqihar University), Qiqihar Heilongjiang 161006, China

Received:2024-04-09 Revised:2024-06-26 Online:2025-03-05 Published:2025-04-02

摘要： 针对蜣螂优化算法存在收敛速度慢,容易陷入局部最优,且全局探索能力较弱等问题,受领导者-追随者策略(leader-follower)的启发,本文提出一种基于邻域搜索策略的蜣螂优化算法。首先,引入Singer映射初始化种群,提高初始解的质量,提高算法的收敛速度;其次,提出一种邻域搜索策略来增强种群多样性,跳出局部收敛,提高算法的局部开发能力;最后,设计一种精英池-扰动策略来扩大搜索范围,增强算法的全局勘探和局部寻优能力,提高算法的求解效率及求解精度。为了验证所提算法的有效性,本文设计一系列实验来验证所提算法的性能,结果表明,该算法在寻优精度和收敛速度方面有较大提升。将该算法应用于无人机三维路径规划问题,实验结果表明,该算法在处理实际应用问题时表现出了有效性和高效性。

关键词: 蜣螂优化算法, 路径规划, Singer映射, 邻域搜索策略, 精英池-扰动策略

Abstract: Taking inspiration from the leader follower strategy, a dung beetle optimization algorithm based on neighborhood search strategy is proposed to address the problems of slow convergence speed, easy falling into local optima, and weak global exploration ability in the optimization algorithm. Firstly, introducing Singer mapping to initialize the population improves the quality of initial solutions and enhances the convergence speed of the algorithm; Secondly, a neighborhood search strategy is proposed to enhance population diversity, break away from local convergence, and improve the local development ability of the algorithm; Finally, an elite pool perturbation strategy is designed to expand the search range, enhance the algorithm’s global exploration and local optimization capabilities, and improve the algorithm’s solving efficiency and accuracy. In order to verify the effectiveness of the proposed algorithm, a series of experiments are designed in this paper to verify its performance. The results indicate that the algorithm has significantly improved optimization accuracy and convergence speed. The algorithm is applied to the three-dimensional path planning problem of unmanned aerial vehicles, and the experimental results show that the algorithm demonstrates effectiveness and efficiency in dealing with practical application problems.

Key words: dung beetle optimization algorithm, path planning, singer mapping, neighborhood search strategy, elite pool-disturbance strategy

中图分类号: TP301.6

杜晓昕, 牛丽明, 王波, 王一萍, 李长荣, 王振飞. 基于邻域搜索策略的蜣螂优化算法及应用[J]. 广西师范大学学报（自然科学版）, 2025, 43(2): 149-167.

DU Xiaoxin, NIU Liming, WANG Bo, WANG Yiping, LI Changrong, WANG Zhenfei. Dung Beetle Optimization Algorithm Based on Neighborhood Search Strategy and Application[J]. Journal of Guangxi Normal University(Natural Science Edition), 2025, 43(2): 149-167.

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