IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v389y2010i9p1922-1930.html
   My bibliography  Save this article

Study on probability distributions for evolution in modified extremal optimization

Author

Listed:
  • Zeng, Guo-Qiang
  • Lu, Yong-Zai
  • Mao, Wei-Jie
  • Chu, Jian

Abstract

It is widely believed that the power-law is a proper probability distribution being effectively applied for evolution in τ-EO (extremal optimization), a general-purpose stochastic local-search approach inspired by self-organized criticality, and its applications in some NP-hard problems, e.g., graph partitioning, graph coloring, spin glass, etc. In this study, we discover that the exponential distributions or hybrid ones (e.g., power-laws with exponential cutoff) being popularly used in the research of network sciences may replace the original power-laws in a modified τ-EO method called self-organized algorithm (SOA), and provide better performances than other statistical physics oriented methods, such as simulated annealing, τ-EO and SOA etc., from the experimental results on random Euclidean traveling salesman problems (TSP) and non-uniform instances. From the perspective of optimization, our results appear to demonstrate that the power-law is not the only proper probability distribution for evolution in EO-similar methods at least for TSP, the exponential and hybrid distributions may be other choices.

Suggested Citation

  • Zeng, Guo-Qiang & Lu, Yong-Zai & Mao, Wei-Jie & Chu, Jian, 2010. "Study on probability distributions for evolution in modified extremal optimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(9), pages 1922-1930.
    • Handle: RePEc:eee:phsmap:v:389:y:2010:i:9:p:1922-1930
    DOI: 10.1016/j.physa.2009.12.055
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437109010693
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2009.12.055?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. Huang, Zhendong & Xiao, Renbin, 2013. "An emergent computation approach to the problem of polygon layout with performance constraints," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(20), pages 5074-5088.
    2. Chen, Yu-Wang & Zhu, Yao-Jia & Yang, Gen-Ke & Lu, Yong-Zai, 2011. "Improved extremal optimization for the asymmetric traveling salesman problem," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4459-4465.

    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:eee:phsmap:v:389:y:2010:i:9:p:1922-1930. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.