Application of collaborative filtering methods in the problem of predicting the performance of population optimization algorithms
- Autores: Ershov N.M.1, Nikitina O.P.1
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Afiliações:
- Lomonosov Moscow State University (MSU)
- Edição: Volume 8, Nº 1 (2021)
- Páginas: 11-25
- Seção: Articles
- URL: https://journals.eco-vector.com/2313-223X/article/view/529809
- DOI: https://doi.org/10.33693/2313-223X-2021-8-1-11-25
- ID: 529809
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Resumo
In this paper we propose an approach to solving the problem of choosing the most efficient algorithm for solving a given continuous optimization problem, based on the using of collaborative filtering methods. A prototype of a software system based on a set of the most popular population optimization algorithms and a system of test objective functions for continuous optimization problems is described. The implementation of several methods for predicting the performance of a given algorithm is considered. The results of computational experiments and comparison of the considered methods are presented.
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Sobre autores
Nikolay Ershov
Lomonosov Moscow State University (MSU)
Email: ershov@gse.cs.msu.ru
Cand. Sci. (Phys.-Math.); senior research associate at the Faculty of Computational Mathematics and Cybernetics Moscow, Russian Federation
Olga Nikitina
Lomonosov Moscow State University (MSU)
Email: nikitinaolga_msu@mail.ru
Faculty of Computational Mathematics and Cybernetics Moscow, Russian Federation
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