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Selection of resilient suppliers has attracted the attention of researchers in the past one decade. The devastating effect of COVID-19 in emerging economies has provided great impetus to the selection of resilient suppliers. Under volatile and uncertain business scenarios, supplier selection is often done under imprecise and incomplete information, making the traditional decision-making methods ineffective. The purpose of this paper is to demonstrate the application of a fuzzy decision-making method for resilient supplier selection.

A group of three decision makers was considered for evaluating various alternatives (suppliers) based on their performance under different primary, sustainability and resilience criteria. Experts' opinion about each criterion and alternative was captured in linguistic terms and was modelled using fuzzy numbers. Then, an algorithm for solving resilient supplier selection problem based on the trapezoidal intuitionistic fuzzy technique for order preference by similarity to ideal solution (TrIFTOPSIS) was introduced and demonstrated through a case study.

A closeness coefficient was used to rank the suppliers based on their distances from intuitionistic fuzzy positive-ideal solution and intuitionistic fuzzy negative-ideal solution. Finally, the proposed fuzzy decision making model was applied to a real problem of supplier selection in the clothing industry.

The presented TrIFTOPSIS model provides an effective route to prioritise and select resilient suppliers under imprecise and incomplete information. This is the first application of intuitionistic fuzzy multi-criteria decision-making for resilient supplier selection.

The main goal of this paper is to develop novel Tω(weakest t-norm)-based fuzzy arithmetic operations to analyze the intuitionistic fuzzy reliability of Printed Circuit Board Assembly (PCBA) using fault tree.

The paper proposes a fuzzy fault tree analysis (FFTA) method for evaluating the intuitionistic fuzzy reliability of any nonrepairable system with uncertain information about failures of system components. This method uses a fault tree for modeling the failure phenomenon of the system, triangular intuitionistic fuzzy numbers (TIFNs) to determine data uncertainty, while novel arithmetic operations are adopted to determine the intuitionistic fuzzy reliability of a system under consideration. The proposed arithmetic operations employ Tω(weakest t-norm) to minimize the accumulating phenomenon of fuzziness, whereas the weighted arithmetic mean is employed to determine the membership as well as nonmembership degrees of the intuitionistic fuzzy failure possibility of the nonrepairable system. The usefulness of the proposed method has been illustrated by inspecting the intuitionistic fuzzy failure possibility of the PCBA and comparing the results with five other existing FFTA methods.

The results show that the proposed FFTA method effectively reduces the accumulating phenomenon of fuzziness and provides optimized degrees of membership and nonmembership for computed intuitionistic fuzzy reliability of a nonrepairable system.

The paper introduces Tω(weakest t-norm) and weighted arithmetic mean based operations for evaluating the intuitionistic fuzzy failure possibility of any nonrepairable system in an uncertain environment using a fault tree.

The purpose of this paper is to propose novel attitudinal prioritization and correlated aggregating methods for multiple attribute group decision making (MAGDM) with triangular intuitionistic fuzzy Choquet integral.

Based on the continuous ordered weighted average (COWA) operator, the triangular fuzzy COWA (TF-COWA) operator is defined, and then a novel attitudinal expected score function for triangular intuitionistic fuzzy numbers (TIFNs) is investigated. The novelty of this function is that it allows the prioritization of TIFNs by taking account of the expert’s attitudinal character. When the ranking order of TIFNs is determined, the triangular intuitionistic fuzzy correlated geometric (TIFCG) operator and the induced TIFCG (I-TIFCG) operator are developed.

Their use is twofold: first, the TIFCG operator is used to aggregate the correlative attribute value; and second, the I-TIFCG operator is designed to aggregate the preferences of experts with some degree of inter-dependent. Then, a TIFCG and I-TIFCG operators-based approach is presented for correlative MAGDM problems. Finally, the propose method is applied to select investment projects.

Based on the TIFCG and I-TIFCG operators, this paper proposes a novel correlated aggregating methods for MAGDM with triangular intuitionistic fuzzy Choquet integral. This method helps to solve the correlated attribute (criteria) relationship. Furthermore, by the attitudinal expected score functions of TIFNs, the propose method can reflect decision maker’s risk attitude in the final decision result.

The triangular intuitionistic fuzzy number (TIFN) is very useful for expressing ill-known quantity. The purpose of this paper is to develop a new method for multi-attribute group decision-making (MAGDM) problems, in which the attribute values are the TIFNs, the attribute weights are completely unknown and the weights of decision makers are given by linguistic variables.

A new method is given to rank TIFNs based on the weighted possibility mean and standard deviation of TIFNs. The weighted Minkowski distance of TIFNs is defined by using the weighted lower and upper possibility means of TIFNs. The weights of experts are determined in terms of the voting model of intuitionistic fuzzy set (IFS). The weights of attributes can be objectively determined through utilizing the information entropy defined by weighted Minkowski distance of TIFNs. Through integrating the attribute weights and expert weights, the collective comprehensive ranking values of alternatives are obtained and used to rank the alternatives.

The stock selection example and comparison analysis show the validity and applicability of the method proposed in this paper.

The paper presents a new ranking method of TIFNs and defines the weighted Minkowski distance of TIFNs. The weights of experts are determined in terms of the voting model of IFS. The weights of attributes can be objectively determined through utilizing the information entropy. The proposed method can greatly enhance the flexibility and agility of decision-making process.

In Iran, the Bank A is one of the largest and most effective banks of the banking network. The continued success of Bank A in improving the economic level of the country and satisfying the customers depends on recognizing all banking activities and processes in the form of supply chain and performing the necessary managerial acts in order to enhance the relevant processes. In this regard, the present study aimed to improve the most effective processes of banking services supply chain of Bank A in Iran.

The present study was applied and descriptive. Research population included the heads, deputies and active experts in Bank A, who were selected through judgmental and saturation sampling methods to complete the questionnaire and participate in interviews and conference sessions. Regarding to aim of study, the integrated approach of intuitionistic fuzzy based DEMATEL-ISM was used.

According to the results, the processes of product delivery, information technology management, public relations and advertising management, risk management, and marketing and sales management exerted the most impacts on other processes in the supply chain. Finally, after designing a process improvement path, solutions were presented to improve the most effective processes.

In this research, efforts were dedicated to the recognition of the major processes of the services supply chain of Bank A, designing the process framework of the bank and improving the prioritized processes by evaluating the causal relations that exist among the processes of the services supply chain.

The purpose of the paper is to bring attention to documentary credits and the efforts to reduce debt obligations in credit history is recognized as an important source of uncommitted bank earnings. Credit risk has a significant impact on the stability of the banking system. This paper identifies the types of credit risk in the banking supply chain.

The authors model the types of credit risk using the intuitive fuzzy failure modes and effects analysis (IFMEA) and intuitive fuzzy cognitive mapping. The population of the study that is needed for the interviews and expert panels comprises senior managers and experts of a leading bank in Iran. The respondents are experienced in credit and banking risk and were selected through judgment sampling and snowballing.

The findings suggest that reducing the risks of the foreign letters of credit contracts can mitigate the risk in the agricultural sector, the specific risks of rent-to-own contracts, the risk of the long-term facilities and the specific risk of the domestic letter of credit contracts.

This research investigates Iran Tejart Bank’s credit risk, formulates a model of the types of credit risk present and analyzes them using the intuitive fuzzy failure modes and effects analysis and intuitive fuzzy cognitive map. Through this credit risk model, one can then facilitate risk management for better financial stability. Also, the model can be used to evaluate the risk indicators.

In the literature, many multi attributes decision making (MADM) models allow evaluation of the alternatives considering their current or last performance. However, in some MADM problems, not only current performance of alternatives but also their past performance should be taken into account in order to select the most appropriate alternative. For this reason, the purpose of this paper is to develop four procedures to evaluate the alternatives in MADM problems with multi terms.

This study uses dynamic operators to aggregate the evaluation in different terms and then, grey relational analysis (GRA) and technique for order preference by similarity to ideal solution (TOPSIS) methods are utilized to determine the most appropriate alternative. Thus, four procedures which consist of these operators and methods are developed to evaluate the alternatives in multi terms.

Some numerical examples are presented for the proposed procedures in multi-terms. Moreover, these four procedures are compared with other four procedures. The analyses of the results show that dynamic aggregation operators based on intuitionistic fuzzy set (IFS) and interval valued intuitionistic fuzzy sets (IVIFS) with GRA and TOPSIS can be used jointly for MADM problems in which alternatives are evaluated for different terms.

One of the significant mistakes faced in some MADM problems is to take into account the current performance of alternatives or is to ignore their past performance. The right selection depends on past and current performance of the alternatives. The novelty of this study is to propose four procedures for solving MADM problems in multi terms based on IFS and IVIFS using dynamic aggregation operators and GRA and TOPSIS methods.

The Chinese believe that “man will conquer the sky” and “fighting with the sky brings endless joy”. Considering that disaster assessment can be regarded as a two-person, zero-sum game problem between nature and human beings, this paper proposes a multi-attribute decision-making method based on game theory and grey theory in a single-value neutrosophic set environment. Due to the complexity and uncertainty of the decision-making environment, the method builds a decision matrix based on single-valued neutrosophic numbers.

First, the authors use the single-value neutrosophic information entropy to calculate the attribute weights and the weighted decision matrix. Second, the optimal mixed strategy method based on linear programming solves the optimal mixed strategy for both sides of the game so that the expected payoff matrix can be obtained. Finally, grey correlation analysis is used to obtain the closeness coefficient of each alternative based on the expectation payoff matrix to identify the ranking result of the alternative.

An example is used to verify the effectiveness of the proposed method, and its rationality is verified through a comprehensive comparison and analysis of the various aspects.

The proposed decision-making method can be applied to typhoon disaster assessment. Such assessment results can provide intelligent decision support to the relevant disaster management departments, thereby reducing the negative impact of typhoon disasters on society, stabilizing society and improving people's happiness. Further, the method can be used for decision-making, recommendation and evaluation in other fields.

The proposed method uses single-value neutrosophic numbers to solve the information representation problem of decision-making in a complex environment. Under a new perspective, game theory is used to handle the decision matrix, while grey relational analysis converts inexact numbers to exact numbers for comparison and sorting. Thus, the proposed method can be used to make reasonable decisions while preserving information to the extent possible.

The purpose of this paper is to develop a methodology based on TODIM (an acronym in Portuguese for interactive and multicriteria decision-making) approach for the selection of the best alternative in the context of multi criteria group decision-making (MCGDM) problems under possibilistic uncertainty in interval-valued Pythagorean fuzzy (IVPF) environment.

In this paper, IVPF-TODIM method is proposed. Some new point operator-based similarity measures (POSMs) for IVPF sets (IVPFSs) are introduced which have the capability to reduce the degree of uncertainty of the elements in the universe of discourse corresponding to IVPFS. Then the newly defined POSMs are used to compute the measure of relative dominance of each alternative over other alternatives in the IVPF-TODIM context. Finally, generalized mean aggregation operator is used to find the best alternative.

As the TODIM method is used to solve the MCGDM problems under uncertainty, POSMs are developed by using three parameters which can control the effect of decision-makers’ psychological perception under risk.

The decision values are used in IVPF numbers (IVPFNs) format.

The proposed method is capable to solve real-life MCGDM problems with not only IVPFNs format but also with interval-valued intuitionistic fuzzy numbers.

As per authors’ concern, no approach using TODIM with IVPFNs is found in literature to solve MCGDM problems under uncertainty. The final judgment values of alternatives using the extended TODIM methodology are highly corroborate in compare to the results of existing methods, which proves its great potentiality in solving MCGDM problems under risk.

In this way, the aim of this study is to expand and evelop the application of this technique in FMEA to rank failure modes of ESQ of academic libraries in an intuitionistic fuzzy environment. Assessment of electronic service quality (ESQ) of libraries is significantly important according to their major roles. It should be noted that the ESQ has a significant impact on customer satisfaction, which improves organizational performance. Accordingly, low ESQ means waste of organizational resources and poor user satisfaction. So, there is a dire need to reflect reasons inducing failure modes in academic library ESQ. Thus, investigation of failure modes affecting academic library ESQ is highly important. One solution in this area is utilization of the intuitionistic fuzzy (IF) failure mode and effects analysis (FMEA) as one of the widely used methods for prediction and identification of failure modes.

The present study in terms of objective is applied and in terms of the type of method is descriptive-analytical. The research sample included four experts of Yazd academic Libraries (Iran). To collect data, three types of questionnaires were distributed among experts. The purpose of the first questionnaire was to identify and reach an agreement on e-library failure modes. Type II questionnaire was used to determine the importance of identified risk factors and Type III questionnaire was used to prioritize the factors.

Results indicate that the difficulty of using websites, lack of provided information feedback to users and lack of links on the website to users' are the main priorities for improving ESQ in the studied academic libraries.

In this approach, the Intuitionistic fuzzy Elimination Et Choix Traduisant la REalité and technique for order of preference by similarity to ideal solution method were used to rank failure modes in academic library ESQ within the FMEA framework.]