Iterative MC-algorithm to solve the global optimization problems
- Autores: Popkov A.Y.1,2, Darkhovsky B.S.1,2,3, Popkov Y.S.1,2,3
-
Afiliações:
- Institute for Systems Analysis
- Moscow Institute of Physics and Technology
- National Research University “Higher School of Economics,”
- Edição: Volume 78, Nº 2 (2017)
- Páginas: 261-275
- Seção: System Analysis and Operations Research
- URL: https://journals.rcsi.science/0005-1179/article/view/150538
- DOI: https://doi.org/10.1134/S0005117917020060
- ID: 150538
Citar
Resumo
A new method was proposed to solve the global minimization problems of the Hölder functions on compact sets obeying continuous functions. The method relies on the Monte Carlo batch processing intended for constructing the sequences of values of the “quasi-global” minima and their decrements. A numerical procedure was proposed to generate a probabilistic stopping rule whose operability was corroborated by numerous tests and benchmarks with algorithmically defined functions.
Palavras-chave
Sobre autores
A. Popkov
Institute for Systems Analysis; Moscow Institute of Physics and Technology
Autor responsável pela correspondência
Email: apopkov@isa.ru
Rússia, Moscow; Dolgoprudnyi
B. Darkhovsky
Institute for Systems Analysis; Moscow Institute of Physics and Technology; National Research University “Higher School of Economics,”
Email: apopkov@isa.ru
Rússia, Moscow; Dolgoprudnyi; Moscow
Yu. Popkov
Institute for Systems Analysis; Moscow Institute of Physics and Technology; National Research University “Higher School of Economics,”
Email: apopkov@isa.ru
Rússia, Moscow; Dolgoprudnyi; Moscow
Arquivos suplementares
