IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-642-00142-0_73.html

MEFISTO: A Pragmatic Metaheuristic Framework for Adaptive Search with a Special Application to Pickup and Delivery Transports

In: Operations Research Proceedings 2008

Author

Listed:
  • Farhad Hassanzadeh

    (Sharif University of Technology, Department of Industrial Engineering)

  • Mohammad Modarres

    (Sharif University of Technology, Department of Industrial Engineering)

  • Mohammad Saffai

    (Sharif University of Technology, Department of Industrial Engineering)

Abstract

Summary Intense competition in the current business environment leads firms to focus on selecting the best R&D project portfolio. Achieving this goal is tied down by uncertainty which is inherent in all R&D projects and therefore, investment decisions must be made within an optimization framework accounting for unavailability of data. In this paper, such a model is developed to hedge against uncertainty. The robust optimization approach is adopted and the problem is formulated as a robust zero-one integer programming model to determine the optimal project portfolio. An example is used to illustrate the benefits of the proposed approach.

Suggested Citation

  • Farhad Hassanzadeh & Mohammad Modarres & Mohammad Saffai, 2009. "MEFISTO: A Pragmatic Metaheuristic Framework for Adaptive Search with a Special Application to Pickup and Delivery Transports," Springer Books, in: Bernhard Fleischmann & Karl-Heinz Borgwardt & Robert Klein & Axel Tuma (ed.), Operations Research Proceedings 2008, chapter 73, pages 451-456, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-00142-0_73
    DOI: 10.1007/978-3-642-00142-0_73
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:spr:sprchp:978-3-642-00142-0_73. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.