• DocumentCode
    1802898
  • Title

    The application of the improved Ant Colony Algorithm in mine locomotive scheduling problem

  • Author

    Guo-ning Gan ; Ting-lei Huang ; Shuai Gao

  • Author_Institution
    School of Computer science and engineering, Guilin University of Electronic Technology, China
  • fYear
    2013
  • fDate
    1-8 Jan. 2013
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Ant Colony Algorithm has some advantages in solving complex optimization problems, in particular discrete optimization problem. A mine locomotive scheduling algorithm based on the improved Ant Colony Algorithm for the mine locomotive scheduling problem has proposed in this paper. The method takes simulated annealing algorithm as a local search strategy of ant colony algorithm, aim at expanding the solution search space, avoiding falling into local optimum that improve convergence rate of the algorithm by dynamic pheromone evaporation factor. Simulation results show that the algorithm is more efficiency in locomotive scheduling than the basic ant colony algorithm.
  • Keywords
    Annealing; Educational institutions; Shafts; Ant Colony Algorithm; Simulated Annealing Algorithm; pheromone; transportation scheduling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Conference Anthology, IEEE
  • Conference_Location
    China
  • Type

    conf

  • DOI
    10.1109/ANTHOLOGY.2013.6784852
  • Filename
    6784852