基于蚁群算法的传感器充电路线规划——考虑有无障碍物影响
Charging Route Planning for Sensors Based on Ant Colony Algorithm—Consider the Presence or Absence of Obstacles
DOI: 10.12677/ORF.2020.104028, PDF,  被引量    国家自然科学基金支持
作者: 陈正浩, 向淑文*, 张 立：贵州大学数学与统计学院，贵州 贵阳
关键词: 蚁群算法；旅行商问题；路径规划；Ant Colony Algorithm； Travel Agent Problem； Path Planning
摘要: 随着物联网的快速发展，无线可充电传感器网络(WRSN)在环境、设备监测等技术应用方面越来越广泛。本文针对移动充电器寻找充电路线最优问题，建立基于蚁周系统的蚁群算法模型，将无障碍的最优路径问题转化为经典旅行商问题。其中，为合理考虑通行道路实际分布情况，加入实际障碍物对道路通行能力的影响，利用蚁群算法寻找各节点间的避障路径组成距离矩阵后，采用最近插入法求解全局最优路径。
Abstract: With the rapid development of Internet of Things, wireless rechargeable sensor network (WRSN) has been widely applied in environmental, device monitoring and other technologies. In this paper, an ant colony algorithm model based on ant week system is established to find the optimal charging route for mobile chargers, and the barrier-free optimal path problem is transformed into the classic travel agent problem. Among them, in order to reasonably consider the actual distribution of the passage road and add the influence of actual obstacles on the road capacity, ant colony algorithm is used to find the obstacle avoidance paths between each node to form the distance matrix, and the nearest insertion method is adopted to solve the global optimal path.
文章引用：陈正浩, 向淑文, 张立. 基于蚁群算法的传感器充电路线规划——考虑有无障碍物影响[J]. 运筹与模糊学, 2020, 10(4): 269-277. https://doi.org/10.12677/ORF.2020.104028

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