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September 10, 2025Scientific ReportsOpen Access

Multi-objective particle swarm algorithm based on angular segmentation archive and dynamic update tactics

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Authors

YLYi LuoYLYanmin LiuJCJianjie Chen

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Overview

ASDMOPSO enhances optimization efficiency in complex problems, suggesting better balance in solution convergence and diversity.

Key Points

  • The ASDMOPSO algorithm improves optimization efficiency significantly.
  • It achieves an average IGD value of 0.032 on the ZDT4 test function, showcasing competitive performance.
  • The approach incorporates a dynamic flight parameter adjustment technique for better exploration and exploitation.
  • Multi-stage initialization using genetic and differential evolutionary algorithms enhances the initial population quality.

Cite This Study

Luo et al. (2025) studied this question.

synapsesocial.com/papers/68c1d02354b1d3bfb60f64b6https://doi.org/10.1038/s41598-025-16539-8
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