• DocumentCode
    2467587
  • Title

    An Evolutionary Algorithm for the Product to Shelf Allocation Problem

  • Author

    Esparcia-Alcázar, Anna I. ; Lluch-Revert, Lidia ; Albarracín-Guillem, José Miguel ; Palmer-Gato, Marta ; Sharman, Ken

  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    3197
  • Lastpage
    3203
  • Abstract
    In this paper we propose an evolutionary algorithm to address the problem of allocating products to shelves in a supermarket (product to shelf allocation problem or P2SAP) and show several instances where it was applied successfully. We first show the main problem exact methods pose, namely bad scalability properties. This means the computational time is of the order of a few minutes for the simplest of cases (one shelf with few modules; few products), while for more complex problems it exceeds 30 hours or, worse still, the method does not provide a solution at all. We then propose an evolutionary algorithm and test it on four different problem configurations (three with one shelf and one with two shelves). In all cases acceptable results can be obtained in a very short timescale.
  • Keywords
    evolutionary computation; retailing; evolutionary algorithm; product allocation; shelf allocation problem; supermarket; Evolutionary computation; Marketing and sales; Scalability; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
  • Conference_Location
    Vancouver, BC
  • Print_ISBN
    0-7803-9487-9
  • Type

    conf

  • DOI
    10.1109/CEC.2006.1688714
  • Filename
    1688714