• DocumentCode
    2909078
  • Title

    A population based hybrid metaheuristic for the p-median problem

  • Author

    Pullan, Wayne

  • Author_Institution
    Sch. of Inf. & Commun. Technol., Griffith Univ., Gold Coast, QLD
  • fYear
    2008
  • fDate
    1-6 June 2008
  • Firstpage
    75
  • Lastpage
    82
  • Abstract
    The p-median problem is one of choosing p facilities from a set of candidates to satisfy the demands of n clients such that the overall cost is minimised. In this paper, PBS, a population based hybrid search algorithm for the p-median problem is introduced. The PBS algorithm uses a genetic algorithm based meta-heuristic, primarily based on cut and paste crossover operators, to generate new starting points for a hybrid local search. For larger p-median instances, PBS is able to effectively utilise a number of computer processors. It is shown empirically that PBS is able to effectively solve p-median problems for a large range of the commonly used p-median benchmark instances.
  • Keywords
    facility location; search problems; hybrid metaheuristic; hybrid search algorithm; p-median problem; population based hybrid metaheuristic; Clustering algorithms; Costs; Genetic algorithms; Helium; High level synthesis; Hybrid power systems; Lagrangian functions; Linear programming; Robustness; Terminology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence). IEEE Congress on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-1822-0
  • Electronic_ISBN
    978-1-4244-1823-7
  • Type

    conf

  • DOI
    10.1109/CEC.2008.4630779
  • Filename
    4630779