IDEAS home Printed from https://ideas.repec.org/a/ids/ijores/v35y2019i1p67-86.html
   My bibliography  Save this article

A pruned Pareto set for multi-objective optimisation problems via particle swarm and simulated annealing

Author

Listed:
  • Ahmad Abubaker
  • Adam Baharum
  • Mahmoud Alrefaei

Abstract

A Pareto optimal set, which is obtained from solving multi-objective optimisation problems, usually contain a large number of optimal solutions. This situation poses a challenge for decision makers in choosing a suitable solution from a large number of overlapping and complex Pareto solutions. This paper proposes a new procedure for solving multi-objective optimisation problems by reducing the size of the Pareto set. The procedure is divided into two major stages. In the first stage, the multi-objective simulated annealing algorithm is used to solve a multi-objective optimisation problem by constructing the Pareto optimal set. In the second stage, the automatic clustering algorithm is used to prune the Pareto set. This procedure is implemented to solve two multi-objective optimisation problems, namely, the 0/1 multi-objective multi-dimensional knapsack problem and the multi-objective inventory system. The procedure enables the decision maker to select an appropriate solution efficiently.

Suggested Citation

  • Ahmad Abubaker & Adam Baharum & Mahmoud Alrefaei, 2019. "A pruned Pareto set for multi-objective optimisation problems via particle swarm and simulated annealing," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 35(1), pages 67-86.
    • Handle: RePEc:ids:ijores:v:35:y:2019:i:1:p:67-86
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=99544
    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:35:y:2019:i:1:p:67-86. 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.