IDEAS home Printed from https://ideas.repec.org/a/igg/joris0/v4y2013i4p96-113.html
   My bibliography  Save this article

Developing a Chance-Constrained Free Disposable Hull Model for Selecting Third-Party Reverse Logistics Providers

Author

Listed:
  • Majid Azadi

    (Department of Industrial Management, Faculty of Management and Accounting, Karaj Branch, Islamic Azad University, Karaj, Iran)

  • Reza Farzipoor Saen

    (Department of Industrial Management, Faculty of Management and Accounting, Karaj Branch, Islamic Azad University, Karaj, Iran)

Abstract

Demand of third-party reverse logistics (3PL) provider becomes an increasingly significant topic for corporations looking for enhanced customer service and cost reduction. To select the best 3PL providers in the presence of stochastic data, this paper proposes an innovative approach which is based on free disposable hull (FDH). FDH model is one of the classical models in data envelopment analysis (DEA). In many real world applications, data are often stochastic. A successful approach to address uncertainty in data is to replace deterministic data via random variables, leading to chance-constrained DEA. In this paper, a chance-constrained FDH (CCFDH) model is developed and also its deterministic equivalent which is a nonlinear program is derived. Furthermore, it is shown that the deterministic equivalent of the CCFDH model can be converted into a quadratic program. In addition, sensitivity analysis of the CCFDH model is discussed with respect to changes on parameters. Finally, a numerical example demonstrates the application of the proposed model in the field of 3PL provider selection.

Suggested Citation

  • Majid Azadi & Reza Farzipoor Saen, 2013. "Developing a Chance-Constrained Free Disposable Hull Model for Selecting Third-Party Reverse Logistics Providers," International Journal of Operations Research and Information Systems (IJORIS), IGI Global, vol. 4(4), pages 96-113, October.
    • Handle: RePEc:igg:joris0:v:4:y:2013:i:4:p:96-113
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijoris.2013100106
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Govindan, Kannan & Kadziński, Miłosz & Ehling, Ronja & Miebs, Grzegorz, 2019. "Selection of a sustainable third-party reverse logistics provider based on the robustness analysis of an outranking graph kernel conducted with ELECTRE I and SMAA," Omega, Elsevier, vol. 85(C), pages 1-15.

    More about this item

    Statistics

    Access and download statistics

    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:igg:joris0:v:4:y:2013:i:4:p:96-113. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    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.