A Multi-population QUasi-Affine TRansformation Evolution Algorithm for Global Optimization

  • Nengxian Liu
  • Jeng-Shyang PanEmail author
  • Xiangwen Liao
  • Guolong Chen
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 834)


In this paper, we propose a new Multi-Population QUasi-Affine TRansformation Evolution (MP-QUATRE) algorithm for global optimization. The proposed MP-QUATRE algorithm divides the population into three sub-populations with a sort strategy to maintain population diversities, and each sub-population adopts a different mutation scheme to make a good balance between exploration and exploitation capability. In the experiments, we compare the proposed algorithm with DE algorithm and QUATRE algorithm on CEC2013 test suite for real-parameter optimization. The experimental results indicate that the proposed MP-QUATRE algorithm has a better performance than the competing algorithms.


QUATRE algorithm Differential evolution Multi-population Global optimization 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Nengxian Liu
    • 1
  • Jeng-Shyang Pan
    • 1
    • 2
    Email author
  • Xiangwen Liao
    • 1
  • Guolong Chen
    • 1
  1. 1.College of Mathematics and Computer ScienceFuzhou UniversityFuzhouChina
  2. 2.Fujian Provincial Key Lab of Big Data Mining and ApplicationsFujian University of TechnologyFuzhouChina

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