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The paper introduces a new mutation operator for genetic algorithms and other similar metaheuristics. This mutation operator is based on the TOPSIS algorithm and is informed by Albert Bandura’s socio-cognitive theory. It incorporates repulsion and attraction mechanisms into gene modifications during mutation, thus making the process dependent on other members of the population. The experimental results on selected popular hard benchmarks are also discussed.

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TOPSIS-Inspired Socio-cognitive Mutation Operator for Metaheuristics

  • 会议论文

  • 发表日期：

    2025年

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  • Jan Bugajski,
  • Tomasz Ukowski,
  • Aleksandra Urbanczyk,
  • Magdalena Krol,
  • Michal Idzik,
  • Marek Kisiel-Dorohinicki,
  • Aleksander Byrski

摘要

The paper introduces a new mutation operator for genetic algorithms and other similar metaheuristics. This mutation operator is based on the TOPSIS algorithm and is informed by Albert Bandura’s socio-cognitive theory. It incorporates repulsion and attraction mechanisms into gene modifications during mutation, thus making the process dependent on other members of the population. The experimental results on selected popular hard benchmarks are also discussed.