Vieno kintamojo funkcijų minimizavimo algoritmų analizė

This paper investigates three methods of one variable function optimizing methods, executes the comparison of their efficiency and generalizes the results of this research. At first there is a review of historical aspects of optimization theory, definition of optimization concept, introduction to t...

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Bibliographic Details
Main Author: Bernotas, Simonas
Other Authors: Dzemyda, Gintautas
Format: Dissertation
Language:Lithuanian
Published: Lithuanian Academic Libraries Network (LABT) 2005
Subjects:
Online Access:http://vddb.library.lt/fedora/get/LT-eLABa-0001:E.02~2005~D_20050622_095038-65797/DS.005.0.01.ETD
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spelling ndltd-LABT_ETD-oai-elaba.lt-LT-eLABa-0001-E.02~2005~D_20050622_095038-657972014-01-17T03:45:46Z2005-06-22litInformaticsBernotas, SimonasVieno kintamojo funkcijų minimizavimo algoritmų analizėAnalysis of one variable functions minimizing methodsLithuanian Academic Libraries Network (LABT)This paper investigates three methods of one variable function optimizing methods, executes the comparison of their efficiency and generalizes the results of this research. At first there is a review of historical aspects of optimization theory, definition of optimization concept, introduction to task formulation. Presentation of optimization importance, the role of objective function in the process of optimization. Introduction to the classification of optimization tasks and optimization of various systems. In this paper there is an analysis of three methods of optimization: “Half distribution”, “Golden cut”, “Powell”. There was created a program for calculating and comparing of the selected optimization methods. During the investigation it was determined that when there is a small precision (0,1; 0,01), the change of minimum of the function and the value of that point are great. When you increase the value of precision the change of minimum of the function and the value of that point are very small. When the precision value is about (0,0001 .. 0,000001) there is a difference in only 6-th – 9-th value after the comma. The use of “Powell” method requires least steps of calculating, the use of “Half distribution” method requires mostly steps of calculating. In about 80 % of calculation the shortest interval of the search was using the “Powell” method of optimizing, in 20 % of calculation the shortest interval of the search was using the “Golden cut” method of optimization... [to full text]Powell methodOptimizavimo metodaiPowell algoritmasOptimizing methodsAuksinio pjūvio metodasGolden cut methodDalinimo pusiau metodasHalf distribution methodMaster thesisDzemyda, GintautasŠaltenis, VydūnasKazlauskas, KazysStankevičienė, EglėVilnius Pedagogical UniversityVilnius Pedagogical Universityhttp://vddb.library.lt/obj/LT-eLABa-0001:E.02~2005~D_20050622_095038-65797LT-eLABa-0001:E.02~2005~D_20050622_095038-65797VPU-LABT20050622-095038-65797http://vddb.library.lt/fedora/get/LT-eLABa-0001:E.02~2005~D_20050622_095038-65797/DS.005.0.01.ETDUnrestrictedapplication/pdf
collection NDLTD
language Lithuanian
format Dissertation
sources NDLTD
topic Informatics
Powell method
Optimizavimo metodai
Powell algoritmas
Optimizing methods
Auksinio pjūvio metodas
Golden cut method
Dalinimo pusiau metodas
Half distribution method
spellingShingle Informatics
Powell method
Optimizavimo metodai
Powell algoritmas
Optimizing methods
Auksinio pjūvio metodas
Golden cut method
Dalinimo pusiau metodas
Half distribution method
Bernotas, Simonas
Vieno kintamojo funkcijų minimizavimo algoritmų analizė
description This paper investigates three methods of one variable function optimizing methods, executes the comparison of their efficiency and generalizes the results of this research. At first there is a review of historical aspects of optimization theory, definition of optimization concept, introduction to task formulation. Presentation of optimization importance, the role of objective function in the process of optimization. Introduction to the classification of optimization tasks and optimization of various systems. In this paper there is an analysis of three methods of optimization: “Half distribution”, “Golden cut”, “Powell”. There was created a program for calculating and comparing of the selected optimization methods. During the investigation it was determined that when there is a small precision (0,1; 0,01), the change of minimum of the function and the value of that point are great. When you increase the value of precision the change of minimum of the function and the value of that point are very small. When the precision value is about (0,0001 .. 0,000001) there is a difference in only 6-th – 9-th value after the comma. The use of “Powell” method requires least steps of calculating, the use of “Half distribution” method requires mostly steps of calculating. In about 80 % of calculation the shortest interval of the search was using the “Powell” method of optimizing, in 20 % of calculation the shortest interval of the search was using the “Golden cut” method of optimization... [to full text]
author2 Dzemyda, Gintautas
author_facet Dzemyda, Gintautas
Bernotas, Simonas
author Bernotas, Simonas
author_sort Bernotas, Simonas
title Vieno kintamojo funkcijų minimizavimo algoritmų analizė
title_short Vieno kintamojo funkcijų minimizavimo algoritmų analizė
title_full Vieno kintamojo funkcijų minimizavimo algoritmų analizė
title_fullStr Vieno kintamojo funkcijų minimizavimo algoritmų analizė
title_full_unstemmed Vieno kintamojo funkcijų minimizavimo algoritmų analizė
title_sort vieno kintamojo funkcijų minimizavimo algoritmų analizė
publisher Lithuanian Academic Libraries Network (LABT)
publishDate 2005
url http://vddb.library.lt/fedora/get/LT-eLABa-0001:E.02~2005~D_20050622_095038-65797/DS.005.0.01.ETD
work_keys_str_mv AT bernotassimonas vienokintamojofunkcijuminimizavimoalgoritmuanalize
AT bernotassimonas analysisofonevariablefunctionsminimizingmethods
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