
Research Article
Double-Stranded Differential Evolution and Particle Swarm Optimization with LibreOffice Nonlinear Programming Solver
@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
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.
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