Egyptian Informatics Journal (Mar 2024)

Dual subpopulation artificial bee colony algorithm based on individual gradation

  • Zhaolu Guo,
  • Hongjin Li,
  • Kangshun Li

Journal volume & issue
Vol. 25
p. 100452

Abstract

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To boost the search performance of Artificial Bee Colony (ABC) algorithm for handling some complicated optimization problems, a dual subpopulation ABC based on individual gradation (DPGABC) is presented. In DPGABC, the whole population is segmented into two subpopulations with different gradations. Then, the subpopulations respectively utilize the strategies with different characteristics as the candidate strategies. So the individuals can exploit the benefits of various strategies to optimize the search performance. Meanwhile, the dual subpopulation mechanism can maintain good population diversity while achieving good convergence performance. In addition, a knowledge-driven parameter update mechanism is designed to improve the convergence performance. The CEC2014 test set is applied for relevant experiments to validate the performance of DPGABC. From the results, DPGABC performs well on most functions.

Keywords