• DocumentCode
    2806026
  • Title

    A Comparison between Scatter Search and the RAND Method for Solving the Joint Replenishment Problem

  • Author

    Gutierrez A., Miguel A. ; de-los-Cobos, S. ; Goddard, J.

  • Author_Institution
    Universidad Autonoma Metropolitana-Iztapalapa, Mexico
  • fYear
    2006
  • fDate
    Nov. 2006
  • Firstpage
    287
  • Lastpage
    295
  • Abstract
    The purpose of the present paper is to compare the performance of scatter search (SS) against one of the best heuristics, known as the RAND algorithm (Kaspi and Rosenblatt [7]), in order to solve a popular and useful multi-product inventory problem referred to in the literature as the joint replenishment problem (JRP). The JRP is a classical problem of great utility for many real problems. This paper applies the SS method to a set of randomly generated examples, and shows that the solutions obtained, when compared to RAND, are, when not better, at least identical in the majority of cases for up to 50 items. An important observation is that the average number of iterations employed by SS to find the best solutions on the set of examples, had a linear behavior with respect to the number of items.
  • Keywords
    Artificial intelligence; Costs; Frequency; Inventory management; Manufacturing; Packaging; Raw materials; Scattering; Silver; Transportation; Joint replenishment problem; RAND algorithm.; scatter search;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence, 2006. MICAI '06. Fifth Mexican International Conference on
  • Conference_Location
    Mexico City, Mexico
  • Print_ISBN
    0-7695-2722-1
  • Type

    conf

  • DOI
    10.1109/MICAI.2006.1
  • Filename
    4022163