Application of collaborative filtering methods in the problem of predicting the performance of population optimization algorithms
( Pp. 11-25)

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Ershov Nikolay M. kandidat fiziko-matematicheskih nauk; starshiy nauchnyy sotrudnik fakulteta vychislitelnoy matematiki i kibernetiki (VMK)
Lomonosov Moscow State University (MSU) Nikitina Olga P. fakultet Vychislitelnoy matematiki i kibernetiki (VMK)
Lomonosov Moscow State University (MSU)
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Abstract:
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.
How to Cite:
Ershov N.M., Nikitina O.P., (2021), APPLICATION OF COLLABORATIVE FILTERING METHODS IN THE PROBLEM OF PREDICTING THE PERFORMANCE OF POPULATION OPTIMIZATION ALGORITHMS. Computational Nanotechnology, 1: 11-25. DOI: 10.33693/2313-223X-2021-8-1-11-25
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Keywords:
recommender systems, optimization, evolutionary algorithms, swarm intelligence methods.