Solving stochastic programming problems using modified differential evolution algorithms
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F12%3A86092944" target="_blank" >RIV/61989100:27240/12:86092944 - isvavai.cz</a>
Výsledek na webu
<a href="http://dx.doi.org/10.1093/jigpal/jzr017" target="_blank" >http://dx.doi.org/10.1093/jigpal/jzr017</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1093/jigpal/jzr017" target="_blank" >10.1093/jigpal/jzr017</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Solving stochastic programming problems using modified differential evolution algorithms
Popis výsledku v původním jazyce
Stochastic (or probabilistic) programming (SP) is an optimization technique in which the constraints and/or the objective function of an optimization problem contain random variables. The mathematical models of these problems may follow any particular probability distribution for model coefficients. The objective here is to determine the proper values for model parameters influenced by random events. In this study, two modified differential evolution (DE) algorithms namely, LDE1 and LDE2 are used for solving SP problems. Two models of SP problems are considered; Stochastic Fractional Programming Problems and Multiobjective Stochastic Linear Programming Problems. The numerical results obtained by the LDE algorithms are compared with the results of basicDE, basic particle swarm optimization (PSO) and the available results from where it is observed that the LDE algorithms significantly improve the quality of solution of the considered problem in comparison with the quoted results in the
Název v anglickém jazyce
Solving stochastic programming problems using modified differential evolution algorithms
Popis výsledku anglicky
Stochastic (or probabilistic) programming (SP) is an optimization technique in which the constraints and/or the objective function of an optimization problem contain random variables. The mathematical models of these problems may follow any particular probability distribution for model coefficients. The objective here is to determine the proper values for model parameters influenced by random events. In this study, two modified differential evolution (DE) algorithms namely, LDE1 and LDE2 are used for solving SP problems. Two models of SP problems are considered; Stochastic Fractional Programming Problems and Multiobjective Stochastic Linear Programming Problems. The numerical results obtained by the LDE algorithms are compared with the results of basicDE, basic particle swarm optimization (PSO) and the available results from where it is observed that the LDE algorithms significantly improve the quality of solution of the considered problem in comparison with the quoted results in the
Klasifikace
Druh
J<sub>x</sub> - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)
CEP obor
IN - Informatika
OECD FORD obor
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Návaznosti výsledku
Projekt
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Návaznosti
S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2012
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Logic journal of IGPL
ISSN
1367-0751
e-ISSN
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Svazek periodika
20
Číslo periodika v rámci svazku
4
Stát vydavatele periodika
GB - Spojené království Velké Británie a Severního Irska
Počet stran výsledku
15
Strana od-do
732-746
Kód UT WoS článku
000306410500010
EID výsledku v databázi Scopus
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