Spatial clustering algorithm with obstacles constraints by QPSO and K-Medoids

The paper proposed a new spatial clustering algorithm with obstacles constraints combined QPSO with K-Medoids named QKSCO in allusion to the disadvantage of the spatial clustering algorithm with obstacles constraints by PSO and K-Medoids,based on the analysis of the existing algorithms of spatial clustering with obstacles constraints.In the space with obstacles constraints,this algorithm used the distance with obstacle to clustering,and introduced QPSO's rapid global convergence to complement the local convergence of K-Medoids algorithm.The experimental results indicated that the new algorithm is more stable than the spatial clustering algorithm with obstacles constrains by particle swarm optimization and K-Medoids,and has better clustering results.