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
相关论文
共 50 条
  • [1] A Chaotic Annealing Neural Network with Gain Sharpening and Its Application to the 0/1 Knapsack Problem
    Baoyun Wang
    Heng Dong
    Zhenya He
    Neural Processing Letters, 1999, 9 : 243 - 247
  • [2] A Chaotic Annealing Neural Network with Gain Sharpening and Its Application to 0-1 Constrained Optimization Problems
    ZHANG Ling hua
    The Journal of China Universities of Posts and Telecommunications, 2000, (03) : 17 - 19
  • [3] Simulated Annealing for the 0/1 Multidimensional Knapsack Problem
    Fubin Qian (School of Management
    and Institute of Economics
    Numerical Mathematics:A Journal of Chinese Universities(English Series), 2007, (04) : 320 - 327
  • [4] ASYMMETRIC NEURAL-NETWORK AND ITS APPLICATION TO KNAPSACK-PROBLEM
    YAMAMOTO, A
    OHTA, M
    UEDA, H
    OGIHARA, A
    FUKUNAGA, K
    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES, 1995, E78A (03) : 300 - 305
  • [5] A Chaotic Neural Network Combined Heuristic Strategy for Multidimensional Knapsack Problem
    Zhou, Ying
    Kuang, Zhanghui
    Wang, Jiahai
    ADVANCES IN COMPUTATION AND INTELLIGENCE, PROCEEDINGS, 2008, 5370 : 715 - 722
  • [6] Improved simulated annealing algorithm solving for 0/1 knapsack problem
    Liu, Aizhen
    Gao, Xiufeng
    Wang, Jiazhen
    Wang, Feng
    Chen, Liyun
    Proceedings of 2006 International Conference on Artificial Intelligence: 50 YEARS' ACHIEVEMENTS, FUTURE DIRECTIONS AND SOCIAL IMPACTS, 2006, : 628 - 631
  • [7] Improved simulated annealing algorithm solving for 0/1 knapsack problem
    Liu, Aizhen
    Wang, Jiazhen
    Han, Guodong
    Wang, Suzhen
    Wen, Jiafu
    ISDA 2006: SIXTH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS, VOL 2, 2006, : 1159 - +
  • [8] Neural Knapsack: A Neural Network Based Solver for the Knapsack Problem
    Nomer, Hazem A. A.
    Alnowibet, Khalid Abdulaziz
    Elsayed, Ashraf
    Mohamed, Ali Wagdy
    IEEE ACCESS, 2020, 8 : 224200 - 224210
  • [9] A flexible annealing chaotic neural network to maximum clique problem
    Yang, Gang
    Tang, Zheng
    Zhang, Zhiqiang
    Zhu, Yunyi
    INTERNATIONAL JOURNAL OF NEURAL SYSTEMS, 2007, 17 (03) : 183 - 192
  • [10] A chaotic annealing neural network and its application to direction estimation of spatial signal sources
    Tan, Y
    Deng, C
    He, ZY
    NEURAL NETWORKS FOR SIGNAL PROCESSING VII, 1997, : 541 - 550
12345