THE METHOD OF FICTITIOUS EXTREMA LOCALIZATION IN THE PROBLEM OF GLOBAL OPTIMIZATION
- 作者: Evtushenko Y.G.1,2, Tret’yakov A.A.1,3
- 
							隶属关系: 
							- Federal Research Center “Informatics and Control” of the Russian Academy of Sciences
- Moscow Institute of Physics and Technology (National Research University)
- Siedlce University, Faculty of Sciences
 
- 期: 卷 512 (2023)
- 页面: 78-80
- 栏目: MATHEMATICS
- URL: https://rjeid.com/2686-9543/article/view/647911
- DOI: https://doi.org/10.31857/S2686954323600222
- EDN: https://elibrary.ru/PNRHVU
- ID: 647911
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详细
The problem of finding the global extremum of a non-negative function on a positive parallelepiped in n-dimensional Euclidean space is considered. A method of fictitious extrema localization in a bounded area near the origin is proposed, which allows to separate the global extremum point from fictitious extrema by discarding it at a significant distance from the localization set of fictitious minima. At the same time, due to the choice of the starting point in the gradient descent method, it is possible to justify the convergence of the iterative sequence to the global extremum of the minimized function.
作者简介
Yu. Evtushenko
Federal Research Center “Informatics and Control” of the Russian Academy of Sciences; Moscow Institute of Physics and Technology (National Research University)
							编辑信件的主要联系方式.
							Email: yuri-evtushenko@yandex.ru
				                					                																			                												                								Russian Federation, Moscow; Russian Federation, Dolgoprudny, Moscow olast						
A. Tret’yakov
Federal Research Center “Informatics and Control” of the Russian Academy of Sciences; Siedlce University, Faculty of Sciences
							编辑信件的主要联系方式.
							Email: prof.tretyakov@gmail.com
				                					                																			                												                								Russian Federation, Moscow; Poland, Siedlce						
参考
- Евтушенко Ю.Г. Методы решения экстремальных задач и их применение в системах оптимизации. М.: Наука, 1982.
- Карманов В.Г. Математическое программирование. М.: Наука, 1986.
- Grishagin V., Israfilov R., Sergeyev Y. Convergence conditions and numerical comparison of global optimization methods based on dimensionality reduction schemes // Applied Mathematics and Computation. 2018. V. 318. P. 270–280.
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