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Multiple routes planning based on particle swarm algorithm and hierarchical clustering

机译:基于粒子群算法和层次聚类的多路径规划

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This paper presents a multiple routes planning algorithm based on particle swarm algorithm (PSO) and hierarchical clustering to overcome the problem of the sensitivity of k-means clustering to the initial clustering center. Firstly, numerous feasible routes are initialed by PSO. Secondly, the model of multiple routes planning based on hierarchical clustering algorithm is designed and the hierarchical clustering is used to divide the initial feasible routes into several categories. Finally, the PSO algorithm is used to find the optimal route of each category, and then the route smooth algorithm is used to get the final optimal route. Simulation results demonstrate the effectiveness of the routes cluster by hierarchical clustering and the feasibility of the algorithm.
机译:为了克服k均值聚类对初始聚类中心的敏感性问题,提出了一种基于粒子群算法(PSO)和层次聚类的多路径规划算法。首先,PSO提出了许多可行的途径。其次,设计了基于层次聚类算法的多路径规划模型,并利用层次聚类将初始可行路径划分为几类。最后,使用PSO算法找到每个类别的最优路径,然后使用路径平滑算法来获得最终的最优路径。仿真结果通过层次聚类证明了路由聚类的有效性和算法的可行性。

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