An Improved Algorithm for TSP Problem Solving with Hopfield Neural Networks

被引：3
|
作者：
An Jinliang [1 ]
Gao Jia [2 ]
Lei Jinhui [1 ]
Gao Guohong [1 ]
机构：
[1] Henan Inst Sci & Technol, Coll Informat Technol, Xinxiang 453003, Peoples R China
[2] Henan Inst Sci & Technol, Coll Human Literauture, Xinxiang 453003, Peoples R China
来源：
SMART MATERIALS AND INTELLIGENT SYSTEMS, PTS 1 AND 2 | 2011年 / 143-144卷
关键词：
Hopfield; TSP; Algorithm; Improved;
D O I：
10.4028/www.scientific.net/AMR.143-144.538
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Hopfield and Tank have shown that neural networks can be used to solve certain computationally hard problems, in particular they studied the Traveling Salesman Problem (TSP). In this paper,on the base of the analysis of tradiontial methord, introduced an improved algorithm for TSP Problem Solving with Hopfield Neural Networks. We found the accuracy of the results depend on the initial parameters to a large extent, discussed how to set initial parameters properly; analysed the internal relationship between the terms in energy function, and improved the energy function. Used a fixed starting point to eliminate the equivalent solution problem,and the number of neurons is reduced from the N2 to (N-1)2. The improved algorithm reduced the unnecessary equivalent solution in calculate process, enhanced the computational efficiency. Experiment results showed that the algorithm improved the speed and the convergence.
引用
收藏
页码：538 / +
页数：2
相关论文
共 50 条
  • [21] Improved Quantum Genetic Algorithm for Solving TSP
    Li XiaoBo
    2011 AASRI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND INDUSTRY APPLICATION (AASRI-AIIA 2011), VOL 2, 2011, : 79 - 82
  • [22] Solving the puzzle problem using Hopfield neural network in conjunction with tree search algorithm
    Taheri, J
    PROCEEDINGS OF THE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS 2003, VOLS 1-4, 2003, : 456 - 461
  • [23] Integrating data transformation techniques with Hopfield neural networks for solving travelling salesman problem
    Jolai, F.
    Ghanbari, A.
    EXPERT SYSTEMS WITH APPLICATIONS, 2010, 37 (07) : 5331 - 5335
  • [24] Hierarchical hopfield neural network in solving the puzzle problem
    Taheri, J
    2004 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-4, PROCEEDINGS, 2004, : 2337 - 2342
  • [25] Improved shuffled frog leaping algorithm for solving TSP
    Luo, Jian-Ping
    Li, Xia
    Shenzhen Daxue Xuebao (Ligong Ban)/Journal of Shenzhen University Science and Engineering, 2010, 27 (02): : 173 - 179
  • [26] An Improved Quantum Genetic Algorithm and The Application in Solving TSP
    Li XiaoBo
    2010 THE 3RD INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND INDUSTRIAL APPLICATION (PACIIA2010), VOL VI, 2010, : 96 - 100
  • [27] An Improved Quantum Genetic Algorithm and The Application in Solving TSP
    Li XiaoBo
    2011 INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION AND INDUSTRIAL APPLICATION (ICIA2011), VOL I, 2011, : 94 - 98
  • [28] An improved ant colony optimization algorithm for solving TSP
    Yue, Yimeng
    Wang, Xin
    International Journal of Multimedia and Ubiquitous Engineering, 2015, 10 (12): : 153 - 164
  • [29] A new imperialist competitive algorithm for solving TSP problem
    Zhang X.-L.
    Chen X.-W.
    Xiao H.
    Li W.
    Zhang, Xin-Long (mtxinlong@126.com), 1600, Northeast University (31): : 586 - 592
  • [30] Problem Solving with Hopfield Networks and Adiabatic Quantum Computing
    Bauckhage, Christian
    Sanchez, Ramses
    Sifa, Rafet
    2020 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2020,
12345