• DocumentCode
    3006434
  • Title

    Quantum-Inspired Evolutionary Algorithm for Transportation Network Design Optimization

  • Author

    Xinping Yan ; Nengchao Lv ; Zhenglin Liu ; Kun Xu

  • Author_Institution
    Eng. Center for Transp. of MOE, Wuhan Univ. of Technol., Wuhan
  • fYear
    2008
  • fDate
    25-26 Sept. 2008
  • Firstpage
    189
  • Lastpage
    192
  • Abstract
    Transportation network design problem deals with how to add or improve some edges on an existing transportation network to improve traffic condition. In this study a bi-level programming model was proposed to optimize the strategy of transportation network capacity improvement in the constraint of budget. The upper level problem aims to minimize the total travel time of all transportation travelers, while the lower level model is users´ equilibrium transportation assignment model. A quantum-inspired evolutionary algorithm was employed to solve the problem. The result of numerical experiment indicated that the proposed model can reduce total travel time by searching optimal solution and the QEA is more efficient than other heuristic algorithm.
  • Keywords
    evolutionary computation; mathematical programming; minimisation; network theory (graphs); quantum computing; road traffic; search problems; transportation; travelling salesman problems; bi-level programming model; budget constraint; equilibrium transportation assignment model; heuristic algorithm; quantum-inspired evolutionary algorithm; search problem; total travel time minimization; traffic condition; transportation network design optimization problem; Design optimization; Evolutionary computation; Heuristic algorithms; Mathematical model; Power engineering and energy; Quantum computing; Roads; Telecommunication traffic; Traffic control; Transportation; Quantum-inspired Evolutionary Algorithm; bi-level programming; network design problem;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Genetic and Evolutionary Computing, 2008. WGEC '08. Second International Conference on
  • Conference_Location
    Hubei
  • Print_ISBN
    978-0-7695-3334-6
  • Type

    conf

  • DOI
    10.1109/WGEC.2008.35
  • Filename
    4637424