A chaotic annealing neural network with gain sharpening and its application to the 0/1 knapsack problem

被引：4
|
作者：
Wang, B
Dong, H
He, ZY
机构：
[1] Nanjing Univ Posts & Telecommun, Dept Informat Engn, Nanjing 210003, Peoples R China
[2] Nanjing Univ Posts & Telecommun, Dept Commun Engn, Nanjing 210003, Peoples R China
[3] Southeast Univ, Dept Radio Engn, Nanjing 210096, Peoples R China
来源：
NEURAL PROCESSING LETTERS | 1999年 / 9卷 / 03期
关键词：
knapsack problem; chaotic annealing; neural network;
D O I：
10.1023/A:1018603904290
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 article we present a modified transiently chaotic neural network model and then use it to solve the 0/1 knapsack problem. During the chaotic searching the gain of the neurons is gradually sharpened, this strategy can accelerate the convergence of the network to a binary state and keep the satisfaction of the constraints. The simulation demonstrates that the approach is efficient both in approximating the global solution and the number of iterations.
引用
收藏
页码：243 / 247
页数：5
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