IDEAS home Printed from https://ideas.repec.org/a/taf/conmgt/v19y2001i6p601-609.html
   My bibliography  Save this article

Genetic algorithm optimization in building portfolio management

Author

Listed:
  • Thomas Tong
  • C. M. Tam
  • Albert Chan

Abstract

A significant proportion of building investment expenditure goes to replacement expenditure for organizations owning a large building stock or portfolio. Over the years, researchers have attempted to develop asset replacement models to aid decision-making in building portfolio management, based upon' a statistical or an heuristic approach. This study attempts to use genetic algorithms to develop models for forecasting long term asset replacement strategies, aiming at smoothing fluctuations of expenditure and resource requirements, and most importantly minimizing the total maintenance and replacement costs. Scenarios are presented to demonstrate how these can be achieved. Further refinement for practical application of the models is also presented.

Suggested Citation

  • Thomas Tong & C. M. Tam & Albert Chan, 2001. "Genetic algorithm optimization in building portfolio management," Construction Management and Economics, Taylor & Francis Journals, vol. 19(6), pages 601-609.
    • Handle: RePEc:taf:conmgt:v:19:y:2001:i:6:p:601-609
    DOI: 10.1080/01446190110062096
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/01446190110062096
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/01446190110062096?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.

    References listed on IDEAS

    as
    1. F. S. C. Lam, 1999. "Scheduling to minimize product design time using a genetic algorithm," International Journal of Production Research, Taylor & Francis Journals, vol. 37(6), pages 1369-1386, April.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Nomeda Dobrovolskienė & Rima Tamošiūnienė, 2015. "An Index to Measure Sustainability of a Business Project in the Construction Industry: Lithuanian Case," Sustainability, MDPI, vol. 8(1), pages 1-14, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.

      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:taf:conmgt:v:19:y:2001:i:6:p:601-609. 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.

      If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RCME20 .

      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.