求解指路标志指引路径规划问题的改进人工蜂群算法

发布时间：2019-05-24 23:43

【摘要】：针对指路标志指引路径规划问题,提出了一种基于改进人工蜂群算法的求解方法。首先,基于路网拓扑表达,对指路标志指引路径规划问题进行论述;其次,考虑指路标志指引路径规划问题的离散型特点,设计了人工蜂群算法求解的具体的方法和步骤;为了提高人工蜂群算法求解指路标志指引路径规划问题的收敛速度和寻优性能,引入遗传交叉因子、精英保留策略和动态侦查蜂机制对传统人工蜂群算法进行改进;最后,选取广州市大学城作为实验区域,将改进的人工蜂群算法用于求解指路标志指引路径规划问题。实验结果表明,改进后的算法有效地解决了传统人工蜂群算法在求解指路标志指引路径规划问题时收敛速度慢、易早熟等的缺陷,更具可行性。
[Abstract]:A method based on improved artificial beehive algorithm is proposed to solve the problem of guiding path planning with guidance signs. Firstly, based on the topological expression of road network, the problem of guiding path planning of guiding signs is discussed. Secondly, considering the discrete characteristics of the problem of guiding path planning of guiding signs, the concrete methods and steps of solving artificial bee swarm algorithm are designed. In order to improve the convergence speed and optimization performance of artificial bee swarm algorithm for guiding path planning problem, genetic cross factor, elite retention strategy and dynamic bee detection mechanism are introduced to improve the traditional artificial bee swarm algorithm. Finally, Guangzhou University City is selected as the experimental area, and the improved artificial bee swarm algorithm is used to solve the path planning problem of guidance signs. The experimental results show that the improved algorithm effectively solves the shortcomings of the traditional artificial bee swarm algorithm in solving the guiding path planning problem of guidance signs, such as slow convergence speed, easy precocious and so on, and is more feasible.
【作者单位】：中山大学工学院广东省智能交通系统重点实验室;
【基金】：广东省科技计划资助项目(2016A020223006,2016B090918038,2015B010110005) 广州市科技计划资助项目(201510010247) 高校基本科研业务费资助项目(15lgpy10)
【分类号】：TP18

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