Titlebook: Recent Developments in the Ordered Weighted Averaging Operators: Theory and Practice; Ronald R. Yager,Janusz Kacprzyk,Gleb Beliakov Book 2

Vital-Signs

The WOWA Operator: A Reviewpermits the aggregation of a set of numerical data with respect to two weighting vectors: one corresponding to the one of the weighted mean and the other corresponding to the one of the OWA. In this chapter we review this operator as well as some of its main results.

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A Review of the OWA Determination Methods: Classification and Some Extensions the OWA operator determination becomes an active topic in recent years. Based on recent developments, the paper give a summary on the OWA determination methods in classification way: the optimization criteria methods, the sample learning methods, the function based methods, the argument dependent m

上腭

Fuzzification of the OWA Operators for Aggregating Uncertain Information with Uncertain Weightsthe aggregation of crisp numbers with crisp weights. However, uncertainty prevails in almost every process of real world decision making, and so there is a need to find OWA mechanisms to aggregate uncertain information. In this chapter, we generalise Yager’s OWA operator and describe two novel uncer

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A Majority Guided Aggregation Operator in Group Decision Makings into account the individual opinions of the decision makers. The concept of majority plays in this context a key role: what is often needed is an overall opinion which synthesizes the opinions of the . of the experts. The reduction of the individual experts’ opinions into a representative value (w

Coeval

Generating OWA Weights from Individual Assessmentshat these weights minimize the disagreement among individual assessments and the outcome provided by the OWA operator. For measuring that disagreement we have aggregated distances between individual and collective assessments by using a metric and an aggregation function. We have paid attention to M

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Applying Linguistic OWA Operators in Consensus Models under Unbalanced Linguistic Informationilarities observed among experts’ opinions. Most GDM problems based on linguistic approaches use symmetrically and uniformly distributed linguistic term sets to express experts’ opinions.However, there exist problemswhose assessments need to be represented by means of unbalanced linguistic term sets

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