• DocumentCode
    3441808
  • Title

    A recurrent neural network for solving the shortest path problem

  • Author

    Wang, Jun

  • Author_Institution
    Dept. of Ind. Technol., North Dakota Univ., Grand Forks, ND, USA
  • Volume
    6
  • fYear
    1994
  • fDate
    30 May-2 Jun 1994
  • Firstpage
    319
  • Abstract
    The shortest path problem is the classical combinatorial optimization problem arising in numerous planning and designing contexts. In this paper, a recurrent neural network for solving the shortest path problem is presented. The proposed recurrent neural network is able to generate optimal solutions to the shortest path problem. The performance and operating characteristics of the recurrent neural network are demonstrated by use of illustrative examples
  • Keywords
    combinatorial mathematics; optimisation; recurrent neural nets; combinatorial optimization problem; operating characteristics; optimal solutions; recurrent neural network; shortest path problem; Costs; Design optimization; Neodymium; Neural networks; Path planning; Recurrent neural networks; Robots; Routing; Shortest path problem; Transportation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1994. ISCAS '94., 1994 IEEE International Symposium on
  • Conference_Location
    London
  • Print_ISBN
    0-7803-1915-X
  • Type

    conf

  • DOI
    10.1109/ISCAS.1994.409590
  • Filename
    409590