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
相关论文
共 50 条
  • [41] Solving the Assignment Problem with the Improved Dual Neural Network
    Hu, Xiaolin
    Wang, Jun
    ADVANCES IN NEURAL NETWORKS - ISNN 2011, PT I, 2011, 6675 : 547 - +
  • [42] The Neural Network for Solving Convex Nonlinear Programming Problem
    Yang, Yongqing
    Xu, Xianyun
    Zhu, Daqi
    INTELLIGENT COMPUTING, PART I: INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING, ICIC 2006, PART I, 2006, 4113 : 494 - 499
  • [43] Neural network models for solving the maximum flow problem
    Effati, S.
    Ranjbar, M.
    APPLICATIONS AND APPLIED MATHEMATICS-AN INTERNATIONAL JOURNAL, 2008, 3 (01): : 149 - 164
  • [44] A neural network for solving job shop scheduling problem
    Abada, A
    Binder, Z
    Ladet, P
    MANAGEMENT AND CONTROL OF PRODUCTION AND LOGISTICS, VOL 1 AND 2, 1998, : 295 - 299
  • [45] A Dual Neural Network Scheme for Solving the Assignment Problem
    Nazemi, Alireza
    Ghezelsofla, Ozra
    COMPUTER JOURNAL, 2017, 60 (03): : 431 - 443
  • [46] Solving maximum clique problem by cellular neural network
    Sengor, NS
    Yalcin, ME
    Cakir, Y
    Ucer, M
    Guzelis, C
    Pekergin, F
    Morgul, O
    ELECTRONICS LETTERS, 1998, 34 (15) : 1504 - 1506
  • [47] 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
  • [48] Integration of new evolutionary approach with artificial neural network for solving short term load forecast problem
    Singh, Priyanka
    Dwivedi, Pragya
    APPLIED ENERGY, 2018, 217 : 537 - 549
  • [49] A Neural Network Model for Solving the Feature Correspondence Problem
    Aboudib, Ala
    Gripon, Vincent
    Coppin, Gilles
    ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING - ICANN 2016, PT II, 2016, 9887 : 439 - 446
  • [50] SOLVING A PLACEMENT PROBLEM BY MEANS OF AN ANALOG NEURAL NETWORK
    KITA, H
    ODANI, H
    NISHIKAWA, Y
    IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 1992, 39 (06) : 543 - 551
12345