An integrated approach for solving a MCDM problem, Combination of Entropy Fuzzy and F-PROMETHEE techniques

Purpose: The intention of this paper is the presentation of a new integrated approach for solving a multi attribute decision making problem by the use of Entropy Fuzzy and F- PROMETHEE (fuzzy preference ranking method for enrichment evaluation) techniques. Design/methodology/approach: In these sorts of multi attribute decision making problem, a number of criteria and alternatives are put forward as input data. Ranking of these alternatives according to mentioned criteria is regarded as the outcome of solving these kinds of problems. Initially, weights of criteria are determined by implementation of Entropy Fuzzy method. According to determined weights, F-PROMETHEE method is exerted to rank these alternatives in terms of desirability of DM (decision maker). Findings: Being in an uncertain environment and vagueness of DM’s judgments, lead us to implement an algorithm which can deal with these constraints properly. This technique namely called Entropy Fuzzy as a weighting method and F-PROMETHEE is performed to fulfill this approach more precisely according to tangible and intangible aspects. The main finding of applied approach is the final ranking of alternatives helping DM to have a more reliable decision. Originality/Value: The main contribution of this approach is the giving real significance to DM’s attitudes about mentioned criteria in determined alternatives which is not elucidate in former approaches like Analytical Hierarchy Process (AHP). Furthermore, previous methods like Shanon Entropy do not pay attention sufficiently to satisfaction degree of each criterion in proposed alternatives, regarding to DM’s statements. Comprehensive explanations about these procedures have been made in miscellaneous sections of this article.Peer Reviewe

A New Type of Compositive Information Entropy for IvIFS and Its Applications

We first show the interval-valued intuitionistic fuzzy entropy which reflects intuitionism and fuzziness of interval-valued intuitionistic fuzzy set (IvIFS) based on interval-valued intuitionistic fuzzy cross-entropy. As for intuitionism and fuzziness of IvIFS, we propose interval-valued intuitionistic entropy and interval-valued fuzzy entropy, respectively. Furthermore, we establish the interval-valued span entropy describing the uncertainty of membership degree and nonmembership degree and show some concrete measure formulas. Combining intuitionistic factor, fuzzy factor, and span factor, we ultimately put forward the axiomatic definition of the compositive entropy and give a measure formula of compositive entropy. In addition, the effectiveness of the compositive entropy measure is illuminated by comparison with other entropy measures. Furthermore, the compositive entropy is applied to multiple attributes’ decision-making by using the weighted correlation coefficient between IvIFSs and pattern recognition by a similarity measure transformed from the compositive entropy

Informational Paradigm, management of uncertainty and theoretical formalisms in the clustering framework: A review

Fifty years have gone by since the publication of the first paper on clustering based on fuzzy sets theory. In 1965, L.A. Zadeh had published “Fuzzy Sets” [335]. After only one year, the first effects of this seminal paper began to emerge, with the pioneering paper on clustering by Bellman, Kalaba, Zadeh [33], in which they proposed a prototypal of clustering algorithm based on the fuzzy sets theory

Development of a TQM-based Framework for Product Infant Failure Assessment

Product infant failures have been traced to the product development and production stage. Researchers and practitioners have opined that total quality management (TQM) can be used to properly managed these failures. While their suggestions have helped in this regard, there is limited information on how to scientifically aggregate criteria that can be used to specifically identify the most suitable TQM technique for product infant failure improvement, especially at the development stage. Hence, this study proposes a fuzzy-based multi-criteria framework for this problem. The framework uses intuitionistic fuzzy set to handle vague and imprecise judgment and Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) to rank selected TQM techniques.  Real-world data sets were used to evaluate the framework performance, while TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) was used to validate the framework performance. Based on the results obtained, the IFWG-VIKOR and TOPSIS methods rank the most and least suitable TQM practices as TM4 and TM11, respectively. The framework can be used to provides insights into the management of techniques that can address infant product failure issues at the early stage of product development.

Pairwise Comparison and Distance Measure of Hesitant Fuzzy Linguistic Term Sets

A hesitant fuzzy linguistic term set (HFLTS), allowing experts using several possible linguistic terms to assess a qualitative linguistic variable, is very useful to express people’s hesitancy in practical decision-making problems. Up to now, a little research has been done on the comparison and distance measure of HFLTSs. In this paper, we present a comparison method for HFLTSs based on pairwise comparisons of each linguistic term in the two HFLTSs. Then, a distance measure method based on the pairwise comparison matrix of HFLTSs is proposed, and we prove that this distance is equal to the distance of the average values of HFLTSs, which makes the distance measure much more simple. Finally, the pairwise comparison and distance measure methods are utilized to develop two multicriteria decision-making approaches under hesitant fuzzy linguistic environments. The results analysis shows that our methods in this paper are more reasonable

A Historical Account of Types of Fuzzy Sets and Their Relationships

In this paper, we review the definition and basic properties of the different types of fuzzy sets that have appeared up to now in the literature. We also analyze the relationships between them and enumerate some of the applications in which they have been used

Measurement of Enterprise Dynamic Capabilities Based on Intuitionistic Fuzzy Sets: Research in Financial Industry

This paper proposes a method of intuitionistic fuzzy sets (IFS) to measure enterprise dynamic capabilities (EDC). It first identifies the key indicators of EDC measurement in financial industry through expert scoring; then it transforms the assessment of language phrase weights and values into the form of intuitionistic fuzzy numbers based on IFS theory; thirdly, it calculates the group comprehensive evaluation and final advantage degree, in order to obtain the dynamic ability score ranking. With an example, the last part is to verify the feasibility and effectiveness of the IFS to apply in measuring dynamic capabilities in 5 enterprises of the financial industry

The legacy of 50 years of fuzzy sets: A discussion

International audienceThis note provides a brief overview of the main ideas and notions underlying fifty years of research in fuzzy set and possibility theory, two important settings introduced by L.A. Zadeh for representing sets with unsharp boundaries and uncertainty induced by granules of information expressed with words. The discussion is organized on the basis of three potential understanding of the grades of membership to a fuzzy set, depending on what the fuzzy set intends to represent: a group of elements with borderline members, a plausibility distribution, or a preference profile. It also questions the motivations for some existing generalized fuzzy sets. This note clearly reflects the shared personal views of its authors

Entropy Measures for Interval-Valued Intuitionistic Fuzzy Sets and Their Application in Group Decision-Making

Entropy measure is an important topic in the fuzzy set theory and has been investigated by many researchers from different points of view. In this paper, two new entropy measures based on the cosine function are proposed for intuitionistic fuzzy sets and interval-valued intuitionistic fuzzy sets. According to the features of the cosine function, the general forms of these two kinds of entropy measures are presented. Compared with the existing ones, the proposed entropy measures can overcome some shortcomings and be used to measure both fuzziness and intuitionism of these two fuzzy sets; as a result, the uncertain information of which can be described more sufficiently. These entropy measures have been applied to assess the experts’ weights and to solve multicriteria fuzzy group decision-making problems