• DocumentCode
    617928
  • Title

    Decomposing Large-Scale Capacitated Arc Routing Problems using a random route grouping method

  • Author

    Yi Mei ; Xiaodong Li ; Xin Yao

  • Author_Institution
    Sch. of Comput. Sci. & Inf. Technol., RMIT Univ., Melbourne, VIC, Australia
  • fYear
    2013
  • fDate
    20-23 June 2013
  • Firstpage
    1013
  • Lastpage
    1020
  • Abstract
    In this paper, a simple but effective Random Route Grouping (RRG) scheme is developed to decompose the LargeScale Capacitated Arc Routing Problem (LSCARP). A theoretical analysis is given to show that the decomposition is guaranteed to be improved by RRG along with the improvement of the best-sofar solution during the search process. Then, RRG is combined with a cooperative co-evolution model to solve LSCARP. The experimental results on the EGL-G LSCARP set showed that given the same computational budget, the proposed approach obtained much better results than its counterpart without using decomposition.
  • Keywords
    evolutionary computation; random processes; search problems; set theory; vehicle routing; EGL-G LSCARP set; RRG scheme; computational budget; cooperative co-evolution model; large-scale capacitated arc routing problem decomposition; random route grouping method; search process; Computer science; Educational institutions; Evolutionary computation; Optimization; Routing; Vectors; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2013 IEEE Congress on
  • Conference_Location
    Cancun
  • Print_ISBN
    978-1-4799-0453-2
  • Electronic_ISBN
    978-1-4799-0452-5
  • Type

    conf

  • DOI
    10.1109/CEC.2013.6557678
  • Filename
    6557678