Solving large scale location problem using affinity propagation clustering

Location problem is a well-studied problem in operations research.By treating location problem as clustering problem,integrating affinity propagation clustering algorithm and mapping information of candidate into feature vector,this paper presented two methods to select suitably situation from candidate situation:location method based on region division and location method based on road network.It evaluated two methods using synthetic data sets as well as real-world data sets.The experimental results show that two methods can solve location problem with fixed number facilities and location problem with unfixed number facilities,and can solve large location problems and provide good solutions.