A Communication Strategy for Paralleling Grey Wolf Optimizer

Tien-Szu Pan, Thi-Kien Dao, Trong-The Nguyen, Shu-Chuan Chu

    Research output: Contribution to journalArticlepeer-review

    20 Citations (Scopus)


    In this paper, a communication strategy for the parallelized Grey Wolf Optimizer is proposed for solving numerical optimization problems. In this proposed method, the population wolves are split into several independent groups based on the original structure of the Grey Wolf Optimizer (GWO), and the proposed communication strategy provides the information flow for the wolves to communicate in different groups. Four benchmark functions are used to test the behavior of convergence, the accuracy, and the speed of the proposed method. According to the experimental results, the proposed communicational strategy increases the speed and accuracy of the GWO on finding the best solution is up to 75% and 45% respectively in comparison with original method.

    Original languageEnglish
    Pages (from-to)253-262
    Number of pages10
    JournalAdvances in Intelligent Systems and Computing
    Publication statusPublished - 2015
    EventThe Ninth International Conference on Genetic and Evolutionary Computing (ICGEC 2015) -
    Duration: 27 Aug 2015 → …


    Dive into the research topics of 'A Communication Strategy for Paralleling Grey Wolf Optimizer'. Together they form a unique fingerprint.

    Cite this