48940

Автор(ы): 

Автор(ов): 

3

Параметры публикации

Тип публикации: 

Статья в журнале/сборнике

Название: 

GFS algorithm based on batch Monte Carlo trials for solving global optimization problems

DOI: 

10.1063/1.4965343

Наименование источника: 

  • AIP Conference Proceedings ( NUMTA-2016 2nd International Conference and Summer School "Numerical Computations:Theory and Algorithms")

Обозначение и номер тома: 

Vol. 1776

Город: 

  • Melville, USA

Издательство: 

  • AIP

Год издания: 

2016

Страницы: 

060009-1--060009-4
Аннотация
A new method for global optimization of H\"older goal functions under compact sets given by inequalities is proposed. All functions are defined only algorithmically. The method is based on performing simple Monte Carlo trials and constructing the sequences of records and the sequence of their decrements. An estimating procedure of H\"{o}lder constants is proposed. Probability estimation of exact global minimum neighborhood using H\"older constants estimates is presented. Results on some analytical and algorithmic test problems illustrate the method's performance.

Библиографическая ссылка: 

Попков Ю.С., Дарховский Б.С., Попков А.Ю. GFS algorithm based on batch Monte Carlo trials for solving global optimization problems // AIP Conference Proceedings ( NUMTA-2016 2nd International Conference and Summer School "Numerical Computations:Theory and Algorithms"). 2016. Vol. 1776. С. 060009-1--060009-4.