Contracting community for computing maximum flow

In this paper, we propose a novel method named Contracting Community Approach (CCA) to get the maximum flow of flow network. Firstly, we contract communities in the original network. Then, we apply classic algorithms on the contracted network to approximately solve the maximum flow problem. Experime...

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Bibliographic Details
Published in2012 IEEE International Conference on Granular Computing pp. 651 - 656
Main Authors Yanping Zhang, Xiansheng Xu, Bo Hua, Shu Zhao
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2012
Subjects
Artificial neural networks
community
contracting
Educational institutions
maximum flow
network
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Summary:In this paper, we propose a novel method named Contracting Community Approach (CCA) to get the maximum flow of flow network. Firstly, we contract communities in the original network. Then, we apply classic algorithms on the contracted network to approximately solve the maximum flow problem. Experimental results show that the efficiency of the proposed algorithm. For sparse networks, the size of network is reduced to 58.38% averagely and the correctness of maximum flow is over 95%. For middle dense networks, the size of network is reduced to 65.77% averagely. For dense networks, the size of network is reduced to 64.84% averagely. And the correctness of maximum flow even reach 100% both in many middle dense and dense cases in our experiments.
ISBN:1467323101
9781467323109
DOI:10.1109/GrC.2012.6468649