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This research introduces a modification to Grey wolf optimizer (GWO) algorithm, aimed at enhancing its effectiveness in solving complex and non-linear optimization problems. The modification involves incorporating an evolutionary factor (EF) into the GWO algorithm to improve its convergence while balancing exploration and exploitation. The modified GWO algorithm was tested on benchmark functions compared to the original GWO along with other algorithms.

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Modified Grey Wolf Optimization Algorithm Using Evolutionary Factor for Global Optimization

  • 会议论文

  • 发表日期：

    2026年

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  • Meenal Beniwal,
  • Ritul Agarwal,
  • Harshit Batra,
  • Vijay Kumar Bohat

摘要

This research introduces a modification to Grey wolf optimizer (GWO) algorithm, aimed at enhancing its effectiveness in solving complex and non-linear optimization problems. The modification involves incorporating an evolutionary factor (EF) into the GWO algorithm to improve its convergence while balancing exploration and exploitation. The modified GWO algorithm was tested on benchmark functions compared to the original GWO along with other algorithms.