Scientific paper ID 2489 : 2024/3
DOUBLE-STRANDED POPULATION IN EVOLUTIONARY ALGORITHMS FOR NONLINEAR PROBLEMS

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

Currently, the supported non-linear solver in LibreOffice Calc is based on a hybrid algorithm for heuristic global optimization. The hybridization is achieved with differential evolution and particle swarm optimization. Natural phenomena like evolution and swarm behavior inspire both algorithms. Such meta-heuristic algorithms are often employed to tackle complex and time-consuming problems where exact numerical methods are not applicable within a reasonable timeframe. Chromosome encoding into classical differential evolution is a much closer abstraction to the RNA structure than the DNA structure. This research proposes a double-stranded (more DNA-like) organization of the chromosomes in the LibreOffice Calc NLP Solver spreadsheet model. The proposed model is validated using two of the most well-known benchmark functions - Rosenbrock and Styblinski-Tang.


двуверижни генетични алгоритми нелинейна оптимизация електронни таблициdouble-stranded genetic algorithms non-linear optimization spreadsheetsGergana Mateeva Delyan Keremedchiev Kalin Kopanov Velizar Varbanov Todor Balabanov

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