Fuzzification of Choquet Integral and its application in multiple criteria decision making

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F10%3A10212134" target="_blank" >RIV/61989592:15310/10:10212134 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Fuzzification of Choquet Integral and its application in multiple criteria decision making

Popis výsledku v původním jazyce

A common approach in the multiple criteria decision making is to obtain the overall evaluation by aggregating the partial evaluations. For this, a member of a large family of aggregation operators is used. Many of these operators commonly employed in decision making (weighted average, ordered weighted average, minimum, maximum, . . . ) can be used only when criteria are independent. On the other hand, the Choquet integral, a generalization of the aforementioned operators, can be used even when some interactions between criteria occur. We present a fuzzified Choquet integral capable of dealing not only with fuzzy partial evaluations first level fuzzification), but also with fuzzy weights (second level fuzzification). We also provide an effective way toevaluate the fully fuzzified integral, which allows its straightforward application to decision making problems with inherent uncertainty.

Název v anglickém jazyce

Fuzzification of Choquet Integral and its application in multiple criteria decision making

Popis výsledku anglicky

A common approach in the multiple criteria decision making is to obtain the overall evaluation by aggregating the partial evaluations. For this, a member of a large family of aggregation operators is used. Many of these operators commonly employed in decision making (weighted average, ordered weighted average, minimum, maximum, . . . ) can be used only when criteria are independent. On the other hand, the Choquet integral, a generalization of the aforementioned operators, can be used even when some interactions between criteria occur. We present a fuzzified Choquet integral capable of dealing not only with fuzzy partial evaluations first level fuzzification), but also with fuzzy weights (second level fuzzification). We also provide an effective way toevaluate the fully fuzzified integral, which allows its straightforward application to decision making problems with inherent uncertainty.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2010

Kód důvěrnosti údajů

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

Název periodika

Neural Network World

ISSN

1210-0552

e-ISSN

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Svazek periodika

20

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

13

Strana od-do

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Kód UT WoS článku

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EID výsledku v databázi Scopus

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