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Genetic algorithms (GAs) are a class of optimization algorithms inspired by natural selection and genetics principles. They have gained significant popularity in various fields due to their ability to solve and optimize complex problems efficiently. This paper provides an overview of GAs, their working principles, applications in problem-solving, and optimization. The paper also discusses the advantages and limitations of GAs and provides insights into future research directions in this field.

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Genetic Algorithm: Unleashing Power of Evolutionary Computing in Problem-Solving and Optimization

  • 会议论文

  • 发表日期：

    2025年

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  • Haohan Zhao,
  • Trong-The Nguyen,
  • Jeng-Shyang Pan,
  • Thi-Kien Dao,
  • Thi-Minh-Phuong Ha,
  • Trinh-Dong Nguyen

摘要

Genetic algorithms (GAs) are a class of optimization algorithms inspired by natural selection and genetics principles. They have gained significant popularity in various fields due to their ability to solve and optimize complex problems efficiently. This paper provides an overview of GAs, their working principles, applications in problem-solving, and optimization. The paper also discusses the advantages and limitations of GAs and provides insights into future research directions in this field.