The Nelder-Mead simplex method with variables partitioning for solving large scale optimization problems

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F14%3A86096563" target="_blank" >RIV/61989100:27240/14:86096563 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-319-01781-5_25" target="_blank" >http://dx.doi.org/10.1007/978-3-319-01781-5_25</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-01781-5_25" target="_blank" >10.1007/978-3-319-01781-5_25</a>

Jazyk výsledku

angličtina

Název v původním jazyce

The Nelder-Mead simplex method with variables partitioning for solving large scale optimization problems

Popis výsledku v původním jazyce

This paper presents a novel method to solve unconstrained continuous optimization problems. The proposed method is called SVP (simplex variables partitioning). The SVP method uses three main processes to solve large scale optimization problems. The firstprocess is a variable partitioning process which helps our method to achieve high performance with large scale and high dimensional optimization problems. The second process is an exploration process which generates a trail solution around a current iterate solution by applying the Nelder-Mead method in a random selected partitions. The last process is an intensification process which applies a local search method in order to refine the the best solution so far. The SVP method starts with a random initial solution, then it is divided into partitions. In order to generate a trail solution, the simplex Nelder-Mead method is applied in each partition by exploring neighborhood regions around a current iterate solution. Finally the intensif

Název v anglickém jazyce

The Nelder-Mead simplex method with variables partitioning for solving large scale optimization problems

Popis výsledku anglicky

This paper presents a novel method to solve unconstrained continuous optimization problems. The proposed method is called SVP (simplex variables partitioning). The SVP method uses three main processes to solve large scale optimization problems. The firstprocess is a variable partitioning process which helps our method to achieve high performance with large scale and high dimensional optimization problems. The second process is an exploration process which generates a trail solution around a current iterate solution by applying the Nelder-Mead method in a random selected partitions. The last process is an intensification process which applies a local search method in order to refine the the best solution so far. The SVP method starts with a random initial solution, then it is divided into partitions. In order to generate a trail solution, the simplex Nelder-Mead method is applied in each partition by exploring neighborhood regions around a current iterate solution. Finally the intensif

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Advances in Intelligent Systems and Computing. Volume 237

ISBN

978-3-319-01780-8

ISSN

2194-5357

e-ISSN

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Počet stran výsledku

14

Strana od-do

271-284

Název nakladatele

Springer

Místo vydání

Basel

Místo konání akce

Ostrava

Datum konání akce

22. 8. 2013

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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