IDEAS home Printed from https://ideas.repec.org/a/ids/ijores/v19y2014i3p358-384.html
   My bibliography  Save this article

An EOQ model of an item with imprecise seasonal time via genetic algorithm

Author

Listed:
  • A.K. Maiti
  • M.K. Maiti
  • M. Maiti

Abstract

Here, an inventory model of an item during its seasonal time is considered where duration of the season of the item is imprecise in nature in non-stochastic sense, i.e., fuzzy in nature. Demand of the item is price dependent and unit cost of the item is time dependent. Unit cost is a decreasing function at the beginning of the season and an increasing function at the end of the season and is constant during the remaining part of the season. The model is formulated to maximise the average proceeds out of the system from the planning horizon which is fuzzy in nature. As optimisation of fuzzy objective is not well defined, optimistic/pessimistic return of the objective function (using possibility/necessity measure of fuzzy event) is optimised. A fuzzy simulation process is proposed to evaluate this optimistic/pessimistic return. A genetic algorithm (GA) is developed based on entropy theory where region of search space gradually decreases to a small neighbourhood of the optima. This is named as region reducing genetic algorithm (RRGA) and is used to solve the model. The model is illustrated with some numerical examples and some sensitivity analyses have been done. In a particular case when planning horizon is crisp the model is solved via RRGA.

Suggested Citation

  • A.K. Maiti & M.K. Maiti & M. Maiti, 2014. "An EOQ model of an item with imprecise seasonal time via genetic algorithm," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 19(3), pages 358-384.
    • Handle: RePEc:ids:ijores:v:19:y:2014:i:3:p:358-384
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=59509
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ids:ijores:v:19:y:2014:i:3:p:358-384. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=170 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.