A learning method in Hopfield neural network for combinatorial optimization problem

被引：0
|
作者：
Rong, LW [1 ]
Zheng, T
Qi, PC
机构：
[1] Toyama Univ, Fac Engn, Toyama 9308555, Japan
[2] Tateyama Syst Inst, Toyama 9300001, Japan
来源：
NEUROCOMPUTING | 2002年 / 48卷
关键词：
combinatorial optimization problems; traveling salesman problem; Hopfield neural network; learning method;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this letter, we utilize the Hopfield network learning method to adjust the balance between constraint term and cost term of the energy function so that the local minimum that the network once falls into vanishes and the network can continue updating in a gradient descent direction of energy. We applied the proposed learning method to the traveling salesman problem to show that the method is capable of finding an optimal solution or a near-optimal solution in a shorter time. (C) 2002 Elsevier Science B.V. All rights reserved.
引用
收藏
页码：1021 / 1024
页数：4
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