IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v108y2001i1p143-15610.1023-a1016059012379.html
   My bibliography  Save this article

A Column Generation Approach to Delivery Planning over Time with Inhomogeneous Service Providers and Service Interval Constraints

Author

Listed:
  • N. Boland
  • T. Surendonk

Abstract

We consider a problem of delivery planning over multiple time periods. Deliveries must be made to customers having nominated demand in each time period. Demand must be met in each time period by use of some combination of inhomogeneous service providers. Each service provider has a different delivery capacity, different cost of delivery to each customer, a different utilisation requirement, and different rules governing the spread of deliveries in time. The problem is to plan deliveries so as to minimise overall costs, subject to demand being met and service rules obeyed. A natural integer programming model was found to be intractable, except on problems with loose demand constraints, with gaps between best lower bound and best feasible solution of up to 35.1%, with an average of 15.4% over the test data set. In all but the problem with loosest demand constraints, Cplex 6.5 applied to this formulation failed to find the optimal solution before running out of memory. However a column generation approach improved the lower bound by between 0.6% and 21.9%, with an average of 9.9%, and in all cases found the optimal solution at the root node, without requiring branching. Copyright Kluwer Academic Publishers 2001

Suggested Citation

  • N. Boland & T. Surendonk, 2001. "A Column Generation Approach to Delivery Planning over Time with Inhomogeneous Service Providers and Service Interval Constraints," Annals of Operations Research, Springer, vol. 108(1), pages 143-156, November.
    • Handle: RePEc:spr:annopr:v:108:y:2001:i:1:p:143-156:10.1023/a:1016059012379
    DOI: 10.1023/A:1016059012379
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1023/A:1016059012379
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1023/A:1016059012379?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    Citations

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


    Cited by:

    1. Tonbari, Mohamed El & Ahmed, Shabbir, 2023. "Consensus-based Dantzig-Wolfe decomposition," European Journal of Operational Research, Elsevier, vol. 307(3), pages 1441-1456.

    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:annopr:v:108:y:2001:i:1:p:143-156:10.1023/a:1016059012379. 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.