Discrete Optimizations using Graph Convolutional Networks

被引：0
|
作者：
Balan, Radu [1 ]
Haghani, Naveed [1 ]
机构：
[1] Univ Maryland, Dept Math, College Pk, MD 20740 USA
来源：
WAVELETS AND SPARSITY XVIII | 2019年 / 11138卷
关键词：
D O I：
10.1117/12.2529432
中图分类号：
O43 [光学];
学科分类号：
070207 ; 0803 ;
摘要：
In this paper we discuss the use of graph deep learning in solving quadratic assignment problems (QAP). The quadratic assignment problem is an NP hard optimization problem. We shall analyze an approach using Graph Convolutional Networks (GCN). We prove that a specially designed GCN produces the optimal solution for a broad class of assignment problems. By appropriate training, the class of problems correctly solved is thus enlarged. Numerical examples compare this method with other simpler methods.
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页数：11
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