Modeling pricing decision problem based on interval type-2 fuzzy theory

2021 ◽  
pp. 1-16
Author(s):  
Huili Pei ◽  
Hongliang Li ◽  
Yankui Liu
Keyword(s):  
Decision Making ◽  
Level Sets ◽  
Fuzzy Variable ◽  
Possibility Distribution ◽  
Fuzzy Variables ◽  
Pricing Decision ◽  
Selection Variable ◽  
Interval Type ◽  
Analytical Expressions

In practical decision-making problems, decision makers are often affected by uncertain parameters because the exact distributions of uncertain parameters are usually difficult to determine. In order to deal with this issue, the major contribution in this paper is to propose a new type of type-2 fuzzy variable called level interval type-2 fuzzy variable from the perspective of level-sets, which is a useful tool in modeling distribution uncertainty. With our level interval type-2 fuzzy variable, we give a method for constructing a parametric level interval (PLI) type-2 fuzzy variable from a nominal possibility distribution by introducing the horizontal perturbation parameters. The proposed horizontal perturbation around the nominal distribution is different from the vertical perturbation discussed in the literature. In order to facilitate the modeling in practical decision-making problems, for a level interval type-2 fuzzy variable, we define its selection variable whose distribution can be determined via its level-sets. The numerical characteristics like expected value and second order moments are important indices in practical optimization and decision-making problems. With this consideration, we establish the analytical expressions about the expected values and second order moments of the selection variables of PLI type-2 trapezoidal, normal and log-normal fuzzy variables. Furthermore, in order to derive the analytical expressions about the numerical characteristics of the selection variable for the sums of the common PLI type-2 fuzzy variables, we discuss the arithmetic about the sums of common PLI type-2 fuzzy variables. Finally, we apply the proposed optimization method to a pricing decision problem to demonstrate the efficiency of our new method. The computational results show that even a small perturbation of the nominal possibility distribution can affect the quality of solutions.

scholarly journals Arithmetic Operations and Expected Values of Regular Interval Type-2 Fuzzy Variables

Symmetry ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2196
Author(s):  
Hui Li ◽  
Junyang Cai
Keyword(s):  
Fuzzy Variable ◽  
Fuzzy Arithmetic ◽  
Computation Complexity ◽  
Arithmetic Operations ◽  
Fuzzy Variables ◽  
Expected Value Operator ◽  
Interval Type ◽  
High Degree ◽  
Mutually Independent

High computation complexity restricts the application prospects of the interval type-2 fuzzy variable (IT2-FV), despite its high degree of freedom in representing uncertainty. Thus, this paper studies the fuzzy operations for the regular symmetric triangular IT2-FVs (RSTIT2-FVs)—the simplest IT2-FVs having the greatest membership degrees of 1. Firstly, by defining the medium of an RSTIT2-FV, its membership function, credibility distribution, and inverse distribution are analytically and explicitly expressed. Secondly, an operational law for fuzzy arithmetic operations regarding mutually independent RSTIT2-FVs is proposed, which can simplify the calculations and directly output the inverse credibility of the functions. Afterwards, the operational law is applied to define the expected value operator of the IT2-FV and prove the linearity of the operator. Finally, some comparative examples are provided to verify the efficiency of the proposed operational law.

A New Method for Solving Multi-Criteria Multi-Attributes Decision Making Based on the Ranking of Type-2 Fuzzy Variables

2021 ◽  
Vol 10 (1) ◽  
pp. 20-42
Author(s):  
Dhiman Dutta ◽  
Mausumi Sen ◽  
Ashok Deshpande ◽  
Biplab Singha
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Ranking Method ◽  
Ranking Methods ◽  
Fuzzy Variables ◽  
Decision Making Problem ◽  
Criteria Weights ◽  
Interval Type ◽  
Very High

In this paper, the authors have proposed the concept of interval type-2 triangular fuzzy variables. Then, they studied the concepts of value and ambiguity of interval type-2 triangular fuzzy variables and interval type-2 trapezoidal fuzzy variables. They introduced the concept of value and ambiguity in order to define the ranking method for the interval type-2 fuzzy variables. A comparative result of the various other ranking methods is also given in the tabular form. A multi-criteria multi-attributes decision-making problem is provided to explain the ranking method in which the evaluation ratings of the alternatives on the attributes, and the criteria weights as provided by the decision makers are expressed as linguistic terms (e.g., very high, medium, fair, and good). The multi-criteria multi-attributes decision-making problem is then worked out by applying the proposed algorithm.

Representing a probabilistic linguistic term set with an interval type-2 fuzzy set and the application in green supplier selection

2021 ◽  
pp. 1-18
Author(s):  
Le Jiang ◽  
Hongbin Liu
Keyword(s):  
Decision Making ◽  
Membership Function ◽  
Fuzzy Set ◽  
Supplier Selection ◽  
Symbolic Model ◽  
Green Supplier Selection ◽  
Linguistic Term ◽  
Interval Type ◽  
Decision Making Model

The use of probabilistic linguistic term sets (PLTSs) means the process of computing with words. The existing methods computing with PLTSs mainly use symbolic model. To provide a semantic model for computing with PLTSs, we propose to represent a PLTS by using an interval type-2 fuzzy set (IT2FS). The key step is to compute the footprint of uncertainty of the IT2FS. To this aim, the upper membership function is computed by aggregating the membership functions of the linguistic terms contained in the PLTS, and the lower membership function is obtained by moving the upper membership function downward with the step being total entropy of the PLTS. The comparison rules, some operations, and an aggregation operator for PLTSs are introduced. Based on the proposed method of computing with PLTSs, a multi-criteria group decision making model is introduced. The proposed decision making model is then applied in green supplier selection problem to show its feasibility.

An interval type-2 hesitant fuzzy best-worst method

2021 ◽  
pp. 1-28
Author(s):  
Ashraf Norouzi ◽  
Hossein Razavi hajiagha
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Group Decision Making ◽  
Group Decision ◽  
Fuzzy Ahp ◽  
Uncertain Data ◽  
Interval Type ◽  
Best Worst Method

Multi criteria decision-making problems are usually encounter implicit, vague and uncertain data. Interval type-2 fuzzy sets (IT2FS) are widely used to develop various MCDM techniques especially for cases with uncertain linguistic approximation. However, there are few researches that extend IT2FS-based MCDM techniques into qualitative and group decision-making environment. The present study aims to adopt a combination of hesitant and interval type-2 fuzzy sets to develop an extension of Best-Worst method (BWM). The proposed approach provides a flexible and convenient way to depict the experts’ hesitant opinions especially in group decision-making context through a straightforward procedure. The proposed approach is called IT2HF-BWM. Some numerical case studies from literature have been used to provide illustrations about the feasibility and effectiveness of our proposed approach. Besides, a comparative analysis with an interval type-2 fuzzy AHP is carried out to evaluate the results of our proposed approach. In each case, the consistency ratio was calculated to determine the reliability of results. The findings imply that the proposed approach not only provides acceptable results but also outperforms the traditional BWM and its type-1 fuzzy extension.

An Interactive Signed Distance Approach for Multiple Criteria Group Decision-Making Based on Simple Additive Weighting Method with Incomplete Preference Information Defined by Interval Type-2 Fuzzy Sets

2014 ◽  
Vol 13 (05) ◽  
pp. 979-1012 ◽  
Author(s):  
Ting-Yu Chen
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Preference Information ◽  
Incomplete Preference ◽  
Signed Distance ◽  
Decision Making Problem ◽  
Simple Additive Weighting ◽  
Interval Type

Interval type-2 fuzzy sets (T2FSs) with interval membership grades are suitable for dealing with imprecision or uncertainties in many real-world problems. In the Interval type-2 fuzzy context, the aim of this paper is to develop an interactive signed distance-based simple additive weighting (SAW) method for solving multiple criteria group decision-making problems with linguistic ratings and incomplete preference information. This paper first formulates a group decision-making problem with uncertain linguistic variables and their transformation to interval type-2 trapezoidal fuzzy numbers. Concerning the relative importance of multiple decision-makers and group consensus of fuzzy opinions, a procedure using hybrid averages is then employed to construct a collective decision matrix. By an appropriate extension of the classical SAW approach, this paper utilizes the concept of signed distances and establishes an integrated programming model to manage multi-criteria group decisions under the incomplete and inconsistent preference structure. Further, an interactive procedure is established for group decision making. Finally, the feasibility and effectiveness of the proposed methods are illustrated by a collaborative decision-making problem of patient-centered care (PCC).

scholarly journals MULTIPLE CRITERIA DECISION ANALYSIS USING PRIORITISED INTERVAL TYPE-2 FUZZY AGGREGATION OPERATORS AND ITS APPLICATION TO SITE SELECTION

2017 ◽  
Vol 23 (1) ◽  
pp. 1-21 ◽  
Author(s):  
Ting-Yu CHEN
Keyword(s):  
Decision Making ◽  
Decision Analysis ◽  
Site Selection ◽  
Aggregation Operator ◽  
Multiple Criteria ◽  
Multiple Criteria Decision Analysis ◽  
Landfill Site Selection ◽  
Fuzzy Aggregation ◽  
Interval Type

The theory of interval type-2 fuzzy sets provides an intuitive and computationally feasible method of addressing uncertain and ambiguous information in decision-making fields. This paper aims to develop a prioritised interval type-2 fuzzy aggregation operator and apply it to multiple criteria decision analysis with prioritised criteria. This paper considers situations in which a relationship between the criteria exists such that a lack of satisfaction by the higher priority criteria cannot be readily compensated by the satisfaction of lower priority criteria. This paper introduces the developed prioritised interval type-2 fuzzy aggregation operator to address the problem of criteria aggregation in this environment. To demonstrate the feasibility of the proposed operator, this paper provides a multiple criteria decision-making method that uses the prioritised interval type-2 fuzzy aggregation operator, and the method is illustrated with a practical application to landfill site selection.

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