Interval type–2 fuzzy decision making

This paper concerns itself with decision making under uncertainty and theconsideration of risk. Type-1 fuzzy logic by its (essentially) crisp nature is limited in modelling decision making as there is no uncertainty in the membership function. We are interested in the role that interval type–2 fuzzy sets might play in enhancing decision making. Previous work by Bellman and Zadeh considered decision making to be based on goals and constraint. They deployed type–1 fuzzy sets. This paper extends this notion to interval type–2 fuzzy sets and presents a new approach to using interval type-2 fuzzy sets in a decision making situation taking into account the risk associated with the decision making. The explicit consideration of risk levels increases the solution space of the decision process and thus enables better decisions. We explain the new approach and provide two examples to show how this new approach works

Comparative Study of Type-1 and Type-2 Fuzzy System in Decision Support System

This study compares the Type-1 Fuzzy and Interval Type-2 Fuzzy in Decision Support System (DSS). Particular case studied in this paper deals with supplier selection for development of new product. DSS is developed to recommend a decision to provide assessment criteria on the supplier. All the type of membership functions and rules between these systems are equally applied. It is shown that  in Type-2 Fuzzy can manage the level of uncertainty in decision making. In general, both systems have a surface resemblance. The result shows that type-2 Fuzzy based decision making with a level of uncertainty is able to provide alternative decisions

Interval type‑2 fuzzy aggregation operator in decision making and its application

Type-2 fuzzy sets (T2FSs) can deal with higher modeling and uncertainties which exist in the real-world application, specifically in the control systems. Particularly the climate changes are always uncertain and thus, the type-2 fuzzy controller is an effective system to handle those situations. Polyhouse is a methodology used to cultivate the plants. It breaks the seasonal hurdle of the formulation and it is also suitable for the conflictive climate conditions. Controlling and directing internal parameters of the polyhouse play an essential role in the growth of the plant. Among those, humidity is an important element when one deals with the growth of the plant in polyhouse. It affects the weather, as well as the global change of the climate and hence, the inner climate of the polyhouse will be disturbed. In this paper, operational laws for triangular interval type-2 fuzzy numbers and derived triangular interval type-2 weighted geometric (TIT2WG) operator with their desired mathematical properties using Dombi triangular norms. Also, humidity control is analyzed using interval type-2 fuzzy controller (IT2FC) with the use of derived aggregation operator which is the aim of the paper. Further stability of the system has been analyzed by applying four different defuzzification methods and the method is recommended which gives a better response

Ranking Causes of Road Accident Occurrence Using Extended Interval Type-2 Fuzzy TOPSIS

Over the past century there has been a dramatic increase in the number of road accidents in Malaysia. Hence, it is necessary to create a decision making method which can consider various preferences and criteria in order to identify the main causes of the accidents. This paper proposes an Interval Type-2 Fuzzy Technique for Order Preference by Similarity to Ideal Solution (IT2FTOPSIS) method which provides a comprehensive valuation from experts. This method is developed based on the aggregation of experts’ opinions on preferred causes of road accidents. The extended IT2FTOPSIS employs a linguistic scales of positive and negative Interval Type-2 Trapezoidal Fuzzy Number (IT2TrFN) and hybrid averaging approach (from an ambiguity and type-reduction methods) to formulate a collective decision environment. Three authorised personnel from three Malaysian Government agencies were interviewed where they were asked to rank the causes. The analysis shows that the linguistic scales of positive and negative Interval Type-2 Trapezoidal Fuzzy Number (IT2TrFN) and hybrid averaging approach are effective in measuring the uncertainties in the interviewees’ responses. Thus this paper concludes that the extended IT2FTOPSIS is more aligned with the users’ decisions compared to the earlier IT2FTOPSIS. Keywords: Multiple criteria decision-making; interval type-2 fuzzy set; IT2FTOPSIS; road accident

MULTI-ATTRIBUTE DECISION MAKING METHOD BASED ON BONFERRONI MEAN OPERATOR AND POSSIBILITY DEGREE OF INTERVAL TYPE-2 TRAPEZOIDAL FUZZY SETS

Abstract. This paper proposes a new approach based on Bonferroni mean operator and possibility degree to solve fuzzy multi-attribute decision making (FMADM) problems in which the attribute value takes the form of interval type-2 fuzzy numbers. We introduce the concepts of interval possibility mean value and present a new method for calculating the possibility degree of two interval trapezoidal type-2 fuzzy sets (IT2 TrFSs). Then, we develop two aggregation techniques, which are called the interval type-2 trapezoidal fuzzy Bonferroni mean (IT2TFBM) operator and the interval type-2 trapezoidal fuzzy weighted Bonferroni mean (IT2TFWBM) operator. We study their properties and discuss their special cases. Based on the IT2TFWBM operator and the possibility degree, a new method of multi-attribute decision making with interval type-2 trapezoidal fuzzy information is proposed. Finally, an illustrative example is given to verify the developed approaches and to demonstrate their practicality and effectiveness

Extension of TOPSIS for Group Decision-Making Based on the Type-2 Fuzzy Positive and Negative Ideal Solutions

Abstract In this paper based on the interval type-2 fuzzy sets, we introduce an extension of fuzzy TOPSIS for handling fuzzy multiple attributes group decision making problems. In the proposed method the fuzzy positive ideal solution and fuzzy negative ideal solution are obtained in the form of interval type-2 fuzzy sets without ranking the elements of decision matrix, using the proposed method the solution of decision problem is obtained with less computational attempt than existing methods

Multiple criteria decision analysis using prioritised interval type-2 fuzzy aggregation operators and its application to site selection

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

IT2-based fuzzy hybrid decision making approach to soft computing

WOS: 000459347800001This aims to evaluate the risk appetite of the financial investors in emerging economies using an integrated interval type-2 fuzzy model. For this purpose, eight different criteria are identified with the supporting literature. The interval type-2 fuzzy DEMAYEL approach is used to weight these criteria regarding the importance level. In addition, investors are classified into three different groups with respect to the risk appetite which are the aggressive/risk taker, moderate/risk neutral, and conservative/risk averse. Moreover, the interval type-2 fuzzy QUALIFLEX methodology is taken into consideration to rank these investor groups. The novelty of this paper is to propose a hybrid fuzzy decision-making approach to the investors' risk appetite based on the interval type-2 fuzzy sets. The findings show that aggressive investors play the most important role in emerging economies. Therefore, financial products, which offer high returns, should be developed to attract the attention of these aggressive investors. Owing to this aspect, it can be possible for emerging economies to improve their financial systems