Graph partition is a classical combinatorial optimization and graph theory problem, and it has a lot of applications, such as scientific computing, VLSI design and clustering etc. In this paper, we study the partition problem on large scale directed graphs under a new objective function, a new instance of graph partition problem. We firstly propose the modeling of this problem, then design an algorithm based on multi-level strategy and recursive partition method, and finally do a lot of simulation experiments. The experimental results verify the stability of our algorithm and show that our algorithm has the same good performance as METIS. In addition, our algorithm is better than METIS on unbalanced ratio.

中文翻译：

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一种新的大规模有向图平衡划分问题的多级算法

图划分是一个经典的组合优化和图论问题，在科学计算、VLSI设计和聚类等方面有着广泛的应用。 本文研究了新目标函数下大规模有向图的划分问题，图划分问题的一个新实例。我们首先提出了这个问题的建模，然后设计了一个基于多级策略和递归划分方法的算法，最后做了大量的仿真实验。实验结果验证了我们算法的稳定性，表明我们的算法具有与METIS相同的良好性能。此外，我们的算法在不平衡比率方面优于 METIS。