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 case 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.

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Posted 30 Mar, 2021
On 23 Apr, 2021
Received 20 Apr, 2021
Received 07 Apr, 2021
On 27 Mar, 2021
Received 25 Mar, 2021
On 25 Mar, 2021
Invitations sent on 24 Mar, 2021
On 23 Mar, 2021
On 23 Mar, 2021
On 22 Mar, 2021
On 22 Mar, 2021
Posted 30 Mar, 2021
On 23 Apr, 2021
Received 20 Apr, 2021
Received 07 Apr, 2021
On 27 Mar, 2021
Received 25 Mar, 2021
On 25 Mar, 2021
Invitations sent on 24 Mar, 2021
On 23 Mar, 2021
On 23 Mar, 2021
On 22 Mar, 2021
On 22 Mar, 2021
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 case 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.

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

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Figure 8

Figure 9

Figure 10
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