Research on Solving Maximum Flow Problem of the Complex Network with Granular Computing
Zhang Yanpin · Journal of Chinese Computer Systems · 2014
Maximum flowproblem is a classical combinational optimization problem. With the growing of the network scale,it is the key issue to get the maximum flowefficiently. For a large-scale complex network,a novel method for getting its maximum flowbased on granular computing is proposed in this paper. Firstly,we granulate the complex network into some sub-networks. Then we compute the maximum flowfor each sub-network. Finally,we compose the maximum flowof each sub-network,and regard it as the estimated maximum flowof the original network. The experimental results on different networks showthe efficiency of the proposed method. The maximum flowerror is only about 1%. At the same time,the running time of our method is 10% of the classical algorithm( the Ford-Fulkerson algorithm) averagely.