دورية أكاديمية
The optimization of multi-UAVs patrol path with hybrid genetic algorithm(基于混合遗传算法的多无人机巡逻路径优化)
| العنوان: | The optimization of multi-UAVs patrol path with hybrid genetic algorithm(基于混合遗传算法的多无人机巡逻路径优化) |
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| المؤلفون: | 李国军(LI Guojun), 郑滋椀(ZHENG Ziwan), 范英盛(FAN Yingsheng), 卢甜甜(LU Tiantian), 徐志江(XU Zhijiang) |
| المصدر: | Zhejiang Daxue xuebao. Lixue ban, Vol 51, Iss 1, Pp 21-28 (2024) |
| بيانات النشر: | Zhejiang University Press, 2024. |
| سنة النشر: | 2024 |
| المجموعة: | LCC:Electronic computers. Computer science LCC:Physics |
| مصطلحات موضوعية: | genetic algorithm(遗传算法), hill-climbing algorithm(爬山算法), patrol(巡逻), path optimization(路径优化), Electronic computers. Computer science, QA75.5-76.95, Physics, QC1-999 |
| الوصف: | Aiming at the optimization of multi-UAVs patrol path, a patrol model of multi-UAVs based on hybrid genetic algorithm is proposed. When constructing the patrol model, each UAV must start from the police station and return to the police station at the end of the patrol. The algorithm is designed by combining traditional genetic algorithm and hill-climbing algorithm. In order to achieve a better optimization effect, the roulette wheel method is employed to select the excellent individuals with higher probability when selecting individuals of the population. In the application of genetic algorithm, the rules of gene crossover and mutation adapted to path optimization are defined. The simulation results show that the proposed hybrid genetic algorithm is significantly better than the traditional genetic algorithm on the optimization effect.(假设无人机巡逻的起、终点均为派出所，提出了一种融合传统遗传算法和爬山算法的警用无人机巡逻路径优化模型——混合遗传算法。按照轮盘赌法则，进行种群个体的选择，以增大优秀种群个体被选中的概率，达到较好的优化效果。同时定义了与路径优化相适应的基因交叉和变异规则。仿真结果表明，提出的混合遗传算法在寻优效果上明显优于传统遗传算法。) |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | Chinese |
| تدمد: | 1008-9497 |
| العلاقة: | https://doaj.org/toc/1008-9497Test |
| DOI: | 10.3785/j.issn.1008-9497.2024.01.004 |
| الوصول الحر: | https://doaj.org/article/e985d1e6adc64239b8afa6cb86338190Test |
| رقم الانضمام: | edsdoj.985d1e6adc64239b8afa6cb86338190 |
| قاعدة البيانات: | Directory of Open Access Journals |
| تدمد: | 10089497 |
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| DOI: | 10.3785/j.issn.1008-9497.2024.01.004 |