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Computer Science and Education in Computer Science. 20th EAI International Conference, CSECS 2024, Sofia, Bulgaria, June 28–30, 2024, Proceedings

Research Article

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

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  • @INPROCEEDINGS{10.1007/978-3-031-84312-9_10,
        author={Gergana Mateeva and Delyan Keremedchiev and Kalin Kopanov and Velizar Varbanov and Todor Balabanov},
        title={Double-Stranded Differential Evolution and Particle Swarm Optimization with LibreOffice Nonlinear Programming Solver},
        proceedings={Computer Science and Education in Computer Science. 20th EAI International Conference, CSECS 2024, Sofia, Bulgaria, June 28--30, 2024, Proceedings},
        proceedings_a={CSECS},
        year={2025},
        month={3},
        keywords={Double-stranded genetic algorithms Nonlinear optimization LibreOffice},
        doi={10.1007/978-3-031-84312-9_10}
    }
    
  • Gergana Mateeva
    Delyan Keremedchiev
    Kalin Kopanov
    Velizar Varbanov
    Todor Balabanov
    Year: 2025
    Double-Stranded Differential Evolution and Particle Swarm Optimization with LibreOffice Nonlinear Programming Solver
    CSECS
    Springer
    DOI: 10.1007/978-3-031-84312-9_10
Gergana Mateeva1, Delyan Keremedchiev2, Kalin Kopanov1, Velizar Varbanov1, Todor Balabanov1,*
  • 1: Bulgarian Academy of Sciences, Institute of Information and Communication Technologies, acad. Georgi Bonchev Street, block 2
  • 2: Department of Informatics, New Bulgarian University, 21 Montevideo Street, block 2
*Contact email: todor.balabanov@iict.bas.bg

Abstract

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.

Keywords
Double-stranded genetic algorithms Nonlinear optimization LibreOffice
Published
2025-03-14
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-84312-9_10
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