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Differential Evolution and Particle Swarm Optimization are heuristic global optimization methods inspired by natural evolution and swarm behavior. They are often used to solve complex optimization and simulation problems that are time-consuming or impossible to solve using exact numerical methods. Traditionally, RNA ideas are closer to Differential Evolution population formation. This paper proposes a double-stranded (more DNA-like) implementation of population in LibreOffice Calc NLP Solver. The proposed implementation is validated with well-known optimization benchmark functions.

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Double-Stranded Differential Evolution and Particle Swarm Optimization with LibreOffice Nonlinear Programming Solver

  • 会议论文

  • 发表日期：

    2025年

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  • Gergana Mateeva,
  • Delyan Keremedchiev,
  • Kalin Kopanov,
  • Velizar Varbanov,
  • Todor Balabanov

摘要

Differential Evolution and Particle Swarm Optimization are heuristic global optimization methods inspired by natural evolution and swarm behavior. They are often used to solve complex optimization and simulation problems that are time-consuming or impossible to solve using exact numerical methods. Traditionally, RNA ideas are closer to Differential Evolution population formation. This paper proposes a double-stranded (more DNA-like) implementation of population in LibreOffice Calc NLP Solver. The proposed implementation is validated with well-known optimization benchmark functions.