Biased experts and similarity based weights in preferences aggregation
نویسندگان
چکیده
In a group decision making setting, we consider the potential impact an expert can have on the overall ranking by providing a biased assessment of the alternatives that differs substantially from the majority opinion. In the framework of similarity based averaging functions, we show that some alternative approaches to weighting the experts’ inputs during the aggregation process can minimize the influence the biased expert is able to exert.
منابع مشابه
A new last aggregation compromise solution approach based on TOPSIS method with hesitant fuzzy setting to energy policy evaluation
Utilizing renewable energies is identified as one of significant issues for economical and social significance in future human life. Thus, choosing the best renewable energy among renewable energy candidates is more important. To address the issue, multi-criteria group decision making (MCGDM) methods with imprecise information could be employed to solve these problems. The aim of this paper is ...
متن کاملThe impact of biased experts in the aggregation of fuzzy preference relations
The group decision making process usually contains a consensus model which focuses on achieving some level of agreement amongst experts before their preferences are aggregated and an alternative is chosen. These consensus models look at the distances between the experts’ preferences and use this to provide each expert with a consensus level. If an expert’s consensus level is below a predefined ...
متن کاملA Concept of Similarity for Intuitionistic Fuzzy Sets and its Use in the Aggregation of Experts’ Testimonies
In this article we apply a new measure of similarity to analyse the extent of agreement in a group of experts. The proposed measure takes into account not only a pure distance between intuitionistic fuzzy preferences but also examines if the compared preferences are more similar or more dissimilar. The agreement of a whole group is assessed via an aggregation of individual testimonies expressed...
متن کاملType-1 OWA operators for aggregating uncertain information with uncertain weights induced by type-2 linguistic quantifiers
The OWA operator proposed by Yager has been widely used to aggregate experts’ opinions or preferences in human decision making. Yager’s traditional OWA operator focuses exclusively on the aggregation of crisp numbers. However, experts usually tend to express their opinions or preferences in a very natural way via linguistic terms. These linguistic terms can be modelled or expressed by (type-1) ...
متن کاملA Linguistic Aggregation operator including weights for Linguistic Values and Experts in Group Decision Making
Different linguistic aggregation methods have been proposed and applied in the linguistic decision making problems. Generally, weights for experts or criteria are considered in linguistic aggregation processes. In this paper, we provide a method to discovery new forms to compute weights and new interpretations in the linguistic ordered weighted averaging operator. In linguistic decision analysi...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2015