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

Title:

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

Creator:

bebčáková , Iveta, Talšová , Jana, and Pavlačka, Ondřej

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:47a8946f-157d-4c3d-86cb-3ccd024cdab7
uuid:47a8946f-157d-4c3d-86cb-3ccd024cdab7

Subject:

Aggregation oparetors, Choquet integral, and fuzzification

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

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 to evaluate the fully fuzzified integral, which allows its straightforward application to decision making problems with inherent uncertainty.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Neural network world: international journal on neural and mass-parallel computing and information systems | 2010 Volume:20 | Number:1

Harvested from:

CDK

Metadata only:

false