IDEAS home Printed from https://ideas.repec.org/a/igg/jamc00/v5y2014i3p1-8.html
   My bibliography  Save this article

Exterior Path Relinking for Zero-One Optimization

Author

Listed:
  • Fred Glover

    (ECEE, School of Engineering & Science, University of Colorado, Boulder, CO, USA)

Abstract

Path relinking (PR) maintains a reference set of elite and diverse solutions, and generates new solutions between and beyond initiating and guiding solutions selected from this set as a foundation for an evolutionary solution process. However, in spite of the widespread application of path relinking in combinatorial optimization, almost all PR implementations only consider the between-form of PR. This note discusses the beyond-form of path relinking, which is called Exterior Path Relinking, and focuses on its relevance for diversification strategies in binary optimization. Finally, this work also observes how to combine the Exterior (beyond) and Interior (between) forms of path relinking.

Suggested Citation

  • Fred Glover, 2014. "Exterior Path Relinking for Zero-One Optimization," International Journal of Applied Metaheuristic Computing (IJAMC), IGI Global, vol. 5(3), pages 1-8, July.
  • Handle: RePEc:igg:jamc00:v:5:y:2014:i:3:p:1-8
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijamc.2014070101
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Ricardo N. Liang & Eduardo A. J. Anacleto & Cláudio N. Meneses, 2022. "Data structures for speeding up Tabu Search when solving sparse quadratic unconstrained binary optimization problems," Journal of Heuristics, Springer, vol. 28(4), pages 433-479, August.
    2. Fernando Stefanello & Vaneet Aggarwal & Luciana S. Buriol & Mauricio G. C. Resende, 2019. "Hybrid algorithms for placement of virtual machines across geo-separated data centers," Journal of Combinatorial Optimization, Springer, vol. 38(3), pages 748-793, October.
    3. Fred Glover & Jin-Kao Hao, 2019. "Diversification-based learning in computing and optimization," Journal of Heuristics, Springer, vol. 25(4), pages 521-537, October.
    4. Yin, Peng-Yeng & Wu, Tsai-Hung & Hsu, Ping-Yi, 2017. "Simulation based risk management for multi-objective optimal wind turbine placement using MOEA/D," Energy, Elsevier, vol. 141(C), pages 579-597.

    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:jamc00:v:5:y:2014:i:3:p:1-8. 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.