scholarly journals MULTI-ATTRIBUTE GROUP DECISION MAKING BASED ON HESITANT FUZZY SETS, TOPSIS METHOD AND FUZZY PREFERENCE RELATIONS

2018 ◽  
Vol 24 (6) ◽  
pp. 2295-2317 ◽  
Author(s):  
Jibin Lan ◽  
Mian Yang ◽  
Mingming Hu ◽  
Fang Liu
Keyword(s):  
Decision Making ◽  
Decision Process ◽  
Group Decision ◽  
Preference Relation ◽  
Order Relation ◽  
Topsis Method ◽  
Fuzzy Preference Relation ◽  
Additive Consistency ◽  
Order Relations ◽  
Fuzzy Preference

Hesitant fuzzy sets (HFSs) are widely applied in pattern recognition, classification, clustering, and multiple attribute decision making. In order to get more accurate decision results, the order relation of HFSs is particularly important. In this paper, some defects of the existing order relations for HFSs are discussed. In order to solve these problems, by employing a distance measure and the TOPSIS method, we propose a new order relation extraction method based on a new additive consistency fuzzy preference relation for hesitant fuzzy elements (HFEs). Then, the proposed additive consistency fuzzy preference relation is applied to integrate group decision information. In multi-attribute group decision making (MAGDM), it is particularly important to ensure the consensus of the decision-makers (DMs), and the consistency of the decision process is the precondition for DMs to reach consensus. The proposed method can maintain the consistency of the decision process for MAGDM under hesitant fuzzy environments, so as to get the consensus of DMs, besides, it can overcome the limitations of the existing order relations for HFSs. At the end of this paper, a numerical example is used to illustrate the effectiveness and feasibility of the new approach, and some comparative analyses are given. The obtained results confirm the theoretical and numerical analyses and emphasize the advantages, which can ensure the consistency of the whole decision process and avoid the original decision information change and loss of the proposed method, so as to be more in line with the actual situation.

scholarly journals Hesitant Probabilistic Fuzzy Preference Relations in Decision Making

2018 ◽  
Vol 2018 ◽  
pp. 1-24 ◽  
Author(s):  
Zia Bashir ◽  
Tabasam Rashid ◽  
Mobashir Iqbal
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Preference Relation ◽  
Decision Makers ◽  
Decision Support Model ◽  
Fuzzy Preference Relation ◽  
Preference Relations ◽  
Hesitant Fuzzy Preference Relation ◽  
Fuzzy Preference

Preference of an alternative over another alternative is a useful way to express the opinion of decision maker. In the process of group decision making, preference relations are used in preference modelling of the alternatives under given criteria. The probability is an important tool to deal with uncertainty; in many scenarios of decision making probabilities of different events affect the decision making process directly. In order to deal with this issue, in this paper, hesitant probabilistic fuzzy preference relation (HPFPR) is defined. Furthermore, consistency of HPFPR and consensus among decision makers are studied in the hesitant probabilistic fuzzy environment. In this respect, many novel algorithms are developed to achieve consistency of HPFPRs and reasonable consensus between decision makers and a final algorithm is proposed comprehending all other algorithms, presenting a complete decision support model for group decision making. Lastly, we present a case study with complete illustration of the proposed model and discussed the effects of probabilities on decision making validating the importance of the introduction of probability in hesitant fuzzy preference relation.

MULTIPLICATIVE CONSISTENCY OF HESITANT FUZZY PREFERENCE RELATION AND ITS APPLICATION IN GROUP DECISION MAKING

2014 ◽  
Vol 13 (01) ◽  
pp. 47-76 ◽  
Author(s):  
HUCHANG LIAO ◽  
ZESHUI XU ◽  
MEIMEI XIA
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Preference Relation ◽  
Aggregation Operators ◽  
Fuzzy Preference Relation ◽  
Multiplicative Consistency ◽  
Hesitant Fuzzy Preference Relation ◽  
Fuzzy Preference Relations ◽  
Fuzzy Preference

As we may have a set of possible values when comparing alternatives (or criteria), the hesitant fuzzy preference relation becomes a suitable and powerful technique to deal with this case. This paper mainly focuses on the multiplicative consistency of the hesitant fuzzy preference relation. First of all, we explore some properties of the hesitant fuzzy preference relation and develop some new aggregation operators. Then we introduce the concepts of multiplicative consistency, perfect multiplicative consistency and acceptable multiplicative consistency for a hesitant fuzzy preference relation, based on which, two algorithms are given to improve the inconsistency level of a hesitant fuzzy preference relation. Furthermore, the consensus of group decision making is studied based on the hesitant fuzzy preference relations. Finally, several illustrative examples are given to demonstrate the practicality of our algorithms.

COMPUTING WITH WORDS IN DECISION MAKING THROUGH INDIVIDUAL AND COLLECTIVE LINGUISTIC CHOICE RULES

2001 ◽  
Vol 09 (supp01) ◽  
pp. 89-102 ◽  
Author(s):  
JANUSZ KACPRZYK ◽  
S£AWOMIR ZADROZNY
Keyword(s):  
Decision Making ◽  
Group Decision ◽  
Preference Relation ◽  
Computing With Words ◽  
Final Solution ◽  
Fuzzy Preference Relation ◽  
Preference Relations ◽  
Fuzzy Preference Relations ◽  
Universal Representation ◽  
Fuzzy Preference

A fuzzy preference relation is a popular model to represent both individual and group preferences. However, what is often sought is a subset of alternatives that is an ultimate solution of a decision problem. In order to arrive at such a final solution individal and/or group choice rules may be employed. There is a wealth of such rules devised in the context of the classical, crisp preference relations. Originally, most of the popular group decision making rules were conceived for classical (crisp) preference relations (orderings), and then extended to the case of traditional fuzzy preference relations. Moreover, they often differ in their assumptions about the properties o the preference relations to be processed. In the paper we pursue the path towards a universal representation of such rules that provides an effective generalization of the classical rules for the fuzzy case. Moreover, it leads to a meaningful extension to the linguistic preferences, in the spirit of the computing with words paradigm.

scholarly journals Compatibility measurement-based group decision making with interval fuzzy preference relations

2016 ◽  
Vol 11 (1) ◽  
pp. 31-39
Author(s):  
Xue-Yang Zhang ◽  
Zhou J Wang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Preference Relation ◽  
Fuzzy Preference Relation ◽  
Interval Numbers ◽  
Preference Relations ◽  
Interval Fuzzy Preference Relation ◽  
Fuzzy Preference Relations ◽  
Fuzzy Preference

In this paper, we put forward a ratio-based compatibility degree between any two ]0,1[-valued interval numbers to measure how proximate they approach to each other. A compatibility measurement is presented to evaluate the compatibility degree between a pair of ]0,1[-valued interval fuzzy preference relations (IFPRs). By employing the geometric mean, a measurement formula is proposed to calculate how close one interval fuzzy preference relation is to all the other interval fuzzy preference relations in a group. We devise an induced interval fuzzy ordered weighted geometric (IIFOWG) operator to aggregate ]0,1[-valued interval numbers, and apply the induced interval fuzzy ordered weighted geometric operator to fuse interval fuzzy preference relations into a collective one. Based on the compatibility measurement between two interval fuzzy preference relations, a notion of acceptable consensus of interval fuzzy preference relations is introduced to check the consensus level between an individual interval fuzzy preference relation and a collective interval fuzzy preference relation, and a novel procedure is developed to handle group decision-making problems with interval fuzzy preference relations. A numerical example with respect to the evaluation of e-commerce websites is provided to illustrate the proposed procedure.

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