改进霜冰优化算法用于数值优化和无人机三维路径规划
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贵州大学现代制造技术教育部重点实验室 贵阳 550025

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TP242;TN911.73

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国家自然科学基金(52165063)、贵州省科技计划资助项目(黔科合支撑[2022]一般165,黔科合支撑[2023]一般309,黔科合支撑[2023]一般348,黔科合支撑[2024]一般 09,黔科合平台人才-CXTD[2023]007,黔科合平台人才-GCC[2022]006-1)、贵阳市科技计划资助项目(筑科合同[2023] 13-11号)资助


Improved rime optimization algorithm for 3D path planning of unmanned aerial vehicles
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Key Laboratory of Modern Manufacturing Technology, Ministry of Education, Guizhou University,Guiyang 550025, China

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    摘要:

    霜冰优化算法(RIME)是一种受霜冰自然生长过程启发的智能优化算法,通过软霜冰策略实现全局搜索,硬霜冰策略实现局部开发,具有较强的寻优能力。然而,RIME在应用中存在收敛速度较慢及易陷入局部最优的问题。为此,本文提出一种改进的霜冰优化算法(IRIME)。首先,在算法的初期引入动态质心引导策略,显著提升了收敛速度;其次,在迭代后期融入改进的差分变异算子,有效降低算法陷入局部最优的风险;此外,设计了一种新的质心边界调整策略,通过深度挖掘种群信息,实现精度和效率的协同优化。基于CEC2017基准测试集的实验表明,IRIME在优化性能上优于PPSO、AGWO、HPHHO、RIME和SRIME。进一步将IRIME应用于无人机三维路径规划问题,结果显示其在解的质量、收敛稳定性和求解效率方面具有显著优势,为复杂工程优化问题提供了一种高效的解决方案。

    Abstract:

    The rime optimization algorithm (RIME) is an intelligent optimization algorithm inspired by the natural growth process of rime. It demonstrates strong optimization capability by employing a soft rime strategy for global search and a hard rime strategy for local exploitation. However, RIME suffers from slow convergence and a tendency to fall into local optima during applications. To address these issues, this paper proposes an improved rime optimization algorithm (IRIME). First, a dynamic centroid guidance strategy is introduced in the early stages of the algorithm, significantly enhancing convergence speed. Second, an improved differential mutation operator is incorporated into the later iterations to effectively reduce the risk of the algorithm becoming trapped in local optima. Additionally, a novel centroid boundary adjustment strategy is designed to enable collaborative optimization of accuracy and efficiency by deeply exploiting population information. Experiments conducted using the CEC2017 benchmark set demonstrate that IRIME outperforms PPSO, AGWO, HPHHO, RIME, and SRIME in optimization performance. Furthermore, IRIME is applied to the three-dimensional path planning problem for UAVs. The results indicate that IRIME provides substantial improvements in solution quality, convergence stability, and computational efficiency, offering an effective solution for complex engineering optimization problems.

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汪家伟,付盛伟,黄海松.改进霜冰优化算法用于数值优化和无人机三维路径规划[J].电子测量技术,2025,48(9):44-55

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  • 在线发布日期: 2025-05-23
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