Multiple routes planning based on particle swarm algorithm and hierarchical clustering
Deyun Zhou, Xiaoyang Li, Kun Zhang, Qian Pan · 2015
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.