Email this article Iterative MC-algorithm to solve the global optimization problems
- Authors: Popkov A.Y.1,2, Darkhovsky B.S.1,2,3, Popkov Y.S.1,2,3
-
Affiliations:
- Institute for Systems Analysis
- Moscow Institute of Physics and Technology
- National Research University “Higher School of Economics,”
- Issue: Vol 78, No 2 (2017)
- Pages: 261-275
- Section: System Analysis and Operations Research
- URL: https://journals.rcsi.science/0005-1179/article/view/150538
- DOI: https://doi.org/10.1134/S0005117917020060
- ID: 150538
Cite item
Open Access
Access granted
Subscription Access
Abstract
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.
About the authors
A. Yu. Popkov
Institute for Systems Analysis; Moscow Institute of Physics and Technology
Author for correspondence.
Email: apopkov@isa.ru
Russian Federation, Moscow; Dolgoprudnyi
B. S. Darkhovsky
Institute for Systems Analysis; Moscow Institute of Physics and Technology; National Research University “Higher School of Economics,”
Email: apopkov@isa.ru
Russian Federation, Moscow; Dolgoprudnyi; Moscow
Yu. S. Popkov
Institute for Systems Analysis; Moscow Institute of Physics and Technology; National Research University “Higher School of Economics,”
Email: apopkov@isa.ru
Russian Federation, Moscow; Dolgoprudnyi; Moscow
Supplementary files
