| 改进型蚁群算法的全局路径规划仿真研究 |
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| 引用本文： | 张鹏,徐晓旭.改进型蚁群算法的全局路径规划仿真研究[J].航空计算技术,2013(6):1-4,8. |
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| 作者姓名： | 张鹏 徐晓旭 |
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| 作者单位： | [1]中国民航大学工程技术训练中心,天津300300 [2]中国民航大学航空自动化学院,天津300300 |
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| 基金项目： | 中国民航总局科技项目资助（MHRD201004） |
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| 摘 要： | 针对传统蚁群算法收敛较慢的问题，提出了一种在复杂环境下全局路径规划的改进型蚁群算法。利用链接图法建立了路径规划的空间模型；借鉴狼群分配原则对信息素进行更新；在缩小搜索区域，提高搜索效率的过程中，引入了启发式概率公式和启发函数；通过参数自适应调整策略，进一步对最优解进行了优化。将基于Dijkstra算法的初始路径规划和改进后蚁群算法的规划结果进行了仿真对比，结果表明，改进后蚁群算法的全局优化性能较好，具有一定的有效性和可行性。
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| 关 键 词： | 全局路径规划 改进型蚁群算法 链接图 启发函数 Dijkstra算法 |
Simulation Research on Global Path Planning Based on Improved Ant Colony Algorithm |
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| Institution: | ZHANG PengI , XU Xiao- xu2 ( 1. Engineering Techniques Training Center, Civil Aviation University of China, Tianfin 300300, China ; 2. Aeronautical Automation College, Civil Aviation University of China, Tianjin 300300, China) |
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| Abstract: | An improved ant colony algorithm on global path planning is presented in a complex environ- ment to solve the problem of slow convergence in traditional ant colony algorithm. Using the MAKLINK graph method to establish a path planning spatial model;drawing the assignment rule of wolf colony to up- date the pheromone;the heuristics probability formula and the heuristic function is introduced in the process of narrowing search areas and improving search efficiency ; furthermore, the optimal solution has been further optimized by parameter adaptive strategy. Finally, the simulation results through comparing the path planning based on Dijkstra algorithm and improved ant algorithm shows that the improved ant colony algorithm has a better global optimization performance, and has a certain effectiveness and feasibil- ity. |
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| Keywords: | global path planning improved ant colony algorithm maklink graph heuristic function Dijk-stra algorithm |
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