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JOURNALS // Avtomatika i Telemekhanika // Archive

Avtomat. i Telemekh., 2017 Issue 2, Pages 82–98 (Mi at14685)

This article is cited in 2 papers

System Analysis and Operations Research

Iterative MC-algorithm to solve the global optimization problems

A. Yu. Popkovab, B. S. Darkhovskyabc, Yu. S. Popkovabc

a Institute for Systems Analysis, Russian Academy of Sciences, Moscow, Russia
b Moscow Institute of Physics and Technology, Dolgoprudnyi, Russia
c National Research University "Higher School of Economics", Moscow, Russia

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.

Keywords: global optimization, batch Monte Carlo iterations, Hölder constants.

Presented by the member of Editorial Board: P. S. Shcherbakov

Received: 27.09.2015


 English version:
Automation and Remote Control, 2017, 78:2, 261–275

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