4.6 Article

Hesitant fuzzy N-soft ELECTRE-II model: a new framework for decision-making

期刊

NEURAL COMPUTING & APPLICATIONS
卷 33, 期 13, 页码 7505-7520

出版社

SPRINGER LONDON LTD
DOI: 10.1007/s00521-020-05498-y

关键词

Star ratings; Decision-making; Hesitant fuzzy N-soft sets; ELECTRE-II

资金

  1. Deanship of Scientific Research (DSR), King Abdulaziz University, Jeddah [3-52/429]

向作者/读者索取更多资源

This article introduces a decision-making framework based on hesitant fuzzy N-soft sets, which is suitable for handling hesitancy in multi-attribute decision-making and proposes an improved method accordingly. The practical application of this method is illustrated through an example of hotel ranking, showcasing its applicability.
In the modelization of frameworks for multi-attribute decision-making, hesitancy embodies a convenient attitude toward undetermined or vague knowledge provided by distinct experts from a group. Hesitant fuzzy N-soft sets are a functional improvement in hesitant fuzzy sets with the practical spirit of N-soft sets. This analytical model accommodates the hesitant situations with evaluations by grades (e.g., in terms of star ratings) and partial degrees of membership. In this article, we approach the problem of selecting alternatives that are described by this model. We advocate for the use of an adapted form of the ELECTRE-II method, that we describe under the name hesitant fuzzy N-soft ELECTRE-II method. With the aim of designing this novel method, we first characterize the notion of hesitant fuzzy N-soft concordance and discordance sets and then construct strong and weak outranking relation, which allow us to rank the objects of the reference set. A practical example concerning the ranking of hotels based on star ratings is fully developed in order to illustrate the applicability of this method. Furthermore, an exhaustive comparison with the hesitant fuzzy N-soft ELECTRE-I and bipolar fuzzy ELECTRE-I methods is performed.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据