The ordered weighted averaging (OWA) operator was introduced by Yager. 1 The fundamental aspect of the OWA operator is a reordering step in which the input arguments are rearranged in descending order. In this article, we propose two new classes of aggregation operators called ordered weighted geome
Ranking of alternatives with ordered weighted averaging operators
β Scribed by M. Teresa Lamata
- Publisher
- John Wiley and Sons
- Year
- 2004
- Tongue
- English
- Weight
- 92 KB
- Volume
- 19
- Category
- Article
- ISSN
- 0884-8173
No coin nor oath required. For personal study only.
β¦ Synopsis
Multiattribute decision making is an important part of the decision process for both individual and group problems. We incorporate the fuzzy set theory and the basic nature of subjectivity due to ambiguity to achieve a flexible decision approach suitable for uncertain and fuzzy environments. Let us consider the analytic hierarchy process (AHP) in which the labels are structured as fuzzy numbers. To obtain the scoring that corresponds to the best alternative or the ranking of the alternatives, we need to use a total order for the fuzzy numbers involved in the problem. In this article, we consider a definition of such a total order, which is based on two subjective aspects: the degree of optimism/pessimism reflected with the ordered weighted averaging (OWA) operators. A numerical example is given to illustrate the approach.
π SIMILAR VOLUMES
We provide a special type of induced ordered weighted averaging (OWA) operator called densityinduced OWA (DIOWA) operator, which takes the density around the arguments as the inducing variables to reorder the arguments. The density around the argument, which can measure the degree of similarity betw
The ordered weighted averaging (OWA) operator by Yager (IEEE Trans Syst Man Cybern 1988; 18; 183-190) has received much more attention since its appearance. One key point in the OWA operator is to determine its associated weights. Among numerous methods that have appeared in the literature, we notic
A problem that we had encountered in the aggregation process is how to aggregate the elements that have cardinality greater than one. The most common operators used in the aggregation process produce reasonable results, but, at the same time, when the items to aggregate have cardinality greater than
The ordered weighted averaging OWA operator of Yager was introduced to provide a method for nonlinearly aggregating a set of input arguments a . A fundamental aspect of i the OWA operator is a reordering step in which the input arguments are rearranged according to their values. Recently, an induced