Solving the Hamiltonian cycle problem via an artificial neural network

被引：4
|
作者：
Tambouratzis, T [1 ]
机构：
[1] NCSR Demokritos, Inst Nucl Tecnol Radiat Protect, Athens 15310, Greece
来源：
INFORMATION PROCESSING LETTERS | 2000年 / 75卷 / 06期
关键词：
combinatorial optimization; maximal constraint satisfaction; graph theory; Hamiltonian cycle; parallel algorithms; artificial neural networks; harmony theory;
D O I：
10.1016/S0020-0190(00)00116-2
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
An artificial neural network (ANN) is proposed for solving the Hamiltonian cycle problem of graph theory. The ANN automatically determines whether the proposed solution constitutes a Hamiltonian cycle. The ANN is also capable of uncovering all the Hamiltonian cycles of the given graph as well as of specifying the origin and direction of the Hamiltonian cycles produced. (C) 2000 Elsevier Science B.V. All rights reserved.
引用
收藏
页码：237 / 242
页数：6
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