Multi-criteria Group Decision Research Articles

Prioritizing real estate enterprises based on credit risk assessment: an integrated multi-criteria group decision support framework

Credit risk assessment involves conducting a fair review and evaluation of an assessed subject’s solvency and creditworthiness. In the context of real estate enterprises, credit risk assessment provides a basis for banks and other financial institutions to choose suitable investment objects. Additionally, it encourages real estate enterprises to abide by market norms and provide reliable information for the standardized management of the real estate industry. However, Chinese real estate companies are hesitant to disclose their actual operating data due to privacy concerns, making subjective evaluation approaches inevitable, occupying important roles in accomplishing Chinese real estate enterprise credit risk assessment tasks. To improve the normative and reliability of credit risk assessment for Chinese real estate enterprises, this study proposes an integrated multi-criteria group decision-making approach. First, a credit risk assessment index for Chinese real estate enterprises is established. Then, the proposed framework combines proportional hesitant fuzzy linguistic term sets and preference ranking organization method for enrichment evaluation II methods. This approach is suitable for processing large amounts of data with high uncertainty, which is often the case in credit risk assessment tasks of Chinese real estate enterprises involving massive subjective evaluation information. Finally, the proposed model is validated through a case study accompanied by sensitivity and comparative analyses to verify its rationality and feasibility. This study contributes to the research on credit assessment for Chinese real estate enterprises and provides a revised paradigm for real estate enterprise credit risk assessment.

A multi-criteria group decision-making method with fuzzy preference relations based on filtration-and-weighting-based triangular bounded consistency

In multi-criteria group decision-making (MCGDM) problems with incomplete fuzzy preference relations (FPRs), the consistency based on bounded rationality is preferred to depend on the historical preferences of decision makers to generate complete FPR matrices. There are two factors in influencing the effect of historical preferences on complete FPR matrices and further decision makers’ satisfaction of group solutions. One is the effectiveness of historical preferences and the other is their relative weights. On this basis, this paper proposes a new MCGDM method with FPRs based on the filtration-and-weighting-based triangular bounded consistency (FWBTBC), where historical FPRs between three adjacent pairs of alternatives are characterized by triangles and these two factors are considered comprehensively. A triangle filtration process is designed based on the Grubbs criterion to filter the abnormal triangles in the collected ones. A weight determination process is developed, where a distance measure between remaining triangles is constructed to calculate their weights. Based on the combination of the two processes, the FWBTBC of FPRs is created and then the proposed method is presented. The validity of the proposed method is demonstrated by its application in analyzing a drainage tube supplier selection problem for a tertiary hospital located in Hefei, Anhui, China.

Complex Fuzzy Rough Aggregation Operators and their Applications in EDAS for Multi-Criteria Group Decision-Making

Complex Fuzzy Rough Aggregation Operators and their Applications in EDAS for Multi-Criteria Group Decision-Making

Cloud model-based best-worst method for group decision making under uncertainty

This study aims to enhance computational and analytical aspects of multi-criteria group decision-making (MCGDM) under uncertainty. For this, we use the best-worst method (BWM) and cloud models to develop a more reliable MCGDM algorithm including three stages: first, collecting data through the BWM reference pairwise comparison; second, extracting interval-weights using the BWM bi-level optimisation models and aggregating different opinions via cloud models; and third, using the technique for order of preference by similarity to ideal solution (TOPSIS) to prioritise alternatives. We have also investigated the effectiveness of the proposed approach in a real-life problem of online learning platform selection within the context of the COVID-19 pandemic lockdown. The experiment results demonstrate the superiority of the proposed method over the Bayesian BWM in terms of computational time by 96%. Moreover, the proposed approach outperforms BWM and Bayesian BWM techniques by 33% and 25%, respectively, in terms of conformity to the decision-makers’ intuitive judgments. Our findings also bring important practical implications. Application of the proposed method led to robustness against the number of decision-makers and significantly increased time efficiency in group decision-making. Besides, the computations with the lower inconsistency enhanced the effectiveness of prioritisation in group decision-making.

Multi-criteria group decision-making based on spherical fuzzy rough numbers

Multi-criteria group decision-making based on spherical fuzzy rough numbers

An interval type-2 fuzzy best-worst method and likelihood-based multi-criteria method in group decision-making

In real-world decision-making problems, a group of decision-makers (DMs) with different levels of expertise gathers to investigate the problem from various perspectives. Making the best choice from an analogous shortlist of competitors is challenging, even for an expert group. To address these types of problems, a new multi-criteria group decision-making (MCGDM) methodology under the interval type-2 trapezoidal fuzzy (IT2TrF) environment is proposed. The proposed IT2TrF MCGDM method comprises three phases. In the first phase, the IT2TrF cognitive best-worst method (IT2TrF-CBWM) is introduced to calculate the initial weights of criteria using the interval scale. Subsequently, a new consistency index (CI) and consistency ratio (CR) are presented. In the second phase, an optimization model is proposed to determine the final IT2TrF weights of criteria. Finally, a likelihood-based method for solving MCGDM problems is introduced in the third phase. The validity of the proposed method is illustrated by addressing a healthcare waste (HCW) treatment technology selection problem during the COVID-19 pandemic. Sensitivity and comparative analyses highlight the superiority and effectiveness of the presented MCGDM method.

Retracted: Novel Distance Measures for Single-Valued Neutrosophic Fuzzy Sets and Their Applications to Multicriteria Group Decision-Making Problem

Retracted: Novel Distance Measures for Single-Valued Neutrosophic Fuzzy Sets and Their Applications to Multicriteria Group Decision-Making Problem

Multi-criteria group decision-making based on the combination of dual hesitant fuzzy sets with soft expert sets for the prediction of a local election scenario

Multi-criteria group decision-making based on the combination of dual hesitant fuzzy sets with soft expert sets for the prediction of a local election scenario

Evaluation of sustainable strategies for urban parcel delivery: Linguistic q-rung orthopair fuzzy Choquet integral approach

For the first time, the critical problem of selecting the most sustainable strategy for urban parcel delivery is addressed and solved in this paper. It aims to help not only postal and logistics companies but also regulatory agencies and city authorities find an environmentally friendly, socially responsible, and economically viable solution. Three alternatives for organizing urban parcel delivery are defined, which are traditional, united consolidation center, and inner-city hubs. According to the three pillars of sustainability, an assessment framework for practitioners is proposed. This paper introduces a linguistic q-rung orthopair fuzzy Choquet integral approach to evaluate sustainable strategies for urban parcel delivery. The linguistic q-rung orthopair fuzzy Choquet integral averaging and linguistic q-rung orthopair fuzzy Choquet integral geometric operators have been constructed for the first time for this purpose. The operator-related qualities are demonstrated. The operators are used to create a multi-criteria group decision-making approach. The case study of the city of Belgrade illustrates the practical applicability of the linguistic q-rung orthopair fuzzy Choquet integral approach. This research findings show that the united consolidation center is the most sustainable strategy for organizing urban parcel delivery.

Multi-criteria group decision-making based on the interval-valued q-rung orthopair fuzzy SIR approach for green supply chain evaluation and selection

Multi-criteria group decision-making based on the interval-valued q-rung orthopair fuzzy SIR approach for green supply chain evaluation and selection

Combining grey relation analysis with MCGDM to evaluate the higher education management quality with interval-valued neutrosophic sets

With the continuous deepening of higher education management reform, university leaders have realized that the merger of universities, annual expansion of enrollment, and expansion of educational scale have broadened the development space for universities. At the same time, many management problems have also emerged, and education management problems are particularly prominent, such as some decisions, plans, instructions, etc. of the school level education management department not being well implemented in various departments, and the channels for the school level education management department to understand the true situation of each department are not smooth. Therefore, deepening reform provides a good opportunity for universities to strengthen management and streamline relationships. Teaching and scientific research must be upgraded, and the quality of teaching management must be improved. Establishing an education management quality evaluation system and emphasizing the quality of education management work are the key. The higher education management quality evaluation is affirmed as multi-criteria group decision-making (MCGDM). Interval-valued neutrosophic sets (IVNSs) have been widely used and researched in MCGDM. The interval-valued neutrosophic sets (IVNSs) could depict the uncertain information within the higher education management quality evaluation. The purpose of this article is to proposed a new improved grey relation analysis (GRA) method based on prospect theory (PT-GRA) to solve the MCGDM under IVNSs. At the end of this paper, an example for higher education management quality evaluation is illustrated through the built method and the comparison. Thus, the main contribution of this study is: (1) the PT-GRA method is used to deal with the MCGDM problems under IVNSs; (2) the weight information is obtained through entropy method; (3) an empirical example for higher education management quality evaluation has been given. (4) some comparative algorithms are given to show the rationality of PT-GRA method with IVNSs.

MABAC method based on cumulative prospect theory for MCGDM with dual probabilistic linguistic term set and applications to sustainable supplier selection

Dual probabilistic linguistic term set (DPLTS) is a new proposed decision-making environment. It uses probabilistic form to represent the appraisal of the alternative from decision makers. There are few methods to deal with DPLTS according to the literature proposed up to now. The purpose of this article is to proposed a new improved Multi-Attribute Border Approximation Area Comparison (MABAC) method extended by cumulative prospect theory (CPT) and combined with DPLTS to address the multi-criteria group decision-making (MCGDM) problem of sustainable supplier selection. In order to make the decision procedure containing more fuzzy information, we also improved the equation of distance between DPLTSs with system of rectangular coordinates. This new improved MABAC method is combined with CPT and it is semi-objective method. Not only in the procedure of calculating distance between alternatives and border approximation area, but also in the procedure of determining the weights of attributes. At the end of this paper, the comparison of this new method with other proposed DPLTS methods, such as Correlation Coefficient Method and DPLTS-TODIM-CRITIC Method, demonstrates the availability and difference.

Three-way group decision based on regret theory under dual hesitant fuzzy environment: An application in water supply alternatives selection

For actual multi-criteria group decision-making (MCGDM) issues with complexity and uncertainty, decision-makers may not be completely rational, and the psychological characteristics generally exert influences on the decision process. As an effective cognitive model, three-way decision (TWD) dedicates to handling uncertainty and is widely used in distinct fields. In this regard, this study incorporates regret emotion into TWD in the dual hesitant fuzzy (DHF) context, and accordingly designs a decision model for uncertain MCGDM issues considering bounded rationality. Specifically, by means of distance measures and score functions of dual hesitant fuzzy elements (DHFEs), the calculation method of loss functions and conditional probability are proposed firstly. Meanwhile, drawing from regret theory, the TWD rules considering regret emotion are generated under the DHF environment. Further, based on this, a detailed three-way group decision model based on regret theory, aimed at solving MCGDM problems under DHF uncertainty, water supply alternatives selection, is constructed. Lastly, a numerical example is employed to elaborate the application of the model.

Multicriteria group decision making approach based on an improved distance measure, the SWARA method and the WASPAS method

Multicriteria group decision making approach based on an improved distance measure, the SWARA method and the WASPAS method

Multi-stage multi-criteria group decision making method based on hierarchical criteria interaction and trust rejection threshold under uncertain preference information

In the face of complex and changeable group decision-making problems, making satisfactory decisions is always difficult, which is deeply affected by information such as different stages, criteria, experts and alternatives. Thus, this study aims to develop an effective multi-stage multi-criteria group decision making (MSMCGDM) method to solve the multi-stage group decision making problems with various information. Firstly, through the introduction of trust rejection threshold, a Cross Calibration method is proposed to calculate experts' weights, considering the social influence of experts in the same stage as well as different stages. Then, based on the extend DEMATEL and Shapley approaches, the DE-Shapley method is constructed to obtain criteria weights considering the hierarchical criteria interaction according to the evaluation information on criteria. Furthermore, inspired by the adjacency matrix, the relationship matrix on alternatives and the concept of alternative sets are proposed to consider the acceptability of alternatives in different stages. Afterwards, elastic mechanism in proposed framework is put forward to deal with the unexpected situations when implementing the optimal alternative set. Finally, two scenarios on snowmelt flood are presented to demonstrate the application of the proposed method, sensitive analysis and comparative analyses are conducted to highlight the advantages of our proposed method.

An indirect multicriteria group decision-making method with heterogeneous preference relations and reliabilities of decision-makers

This study proposes a new indirect method to solve multicriteria group decision-making (MCGDM) problems with heterogeneous preference relations and decision-makers’ reliabilities. To unify the heterogeneous preference relations, the transformation of multiplicative preference relations (MPRs), fuzzy preference relations (FPRs), intuitionistic fuzzy preference relations (IFPRs), and linguistic preference relations (LPRs) into distributed preference relations (DPRs) is analyzed. As consistency among DPRs is constructed under the assumption that decision-makers are bounded rationality, the abstract transformation of MPR, FPR, IFPR, and LPR into DPR is defined, and its reality depends on the preferences of decision-makers. Two important properties of abstract transformation, namely, internal consistency and restricted max-max transitivity, were theoretically verified. The reliabilities of decision-makers are involved in MCGDM by estimating the reliability of each criterion to improve solution quality. Based on the four types of abstract transformations, a process for analyzing MCGDM problems with heterogeneous preference relations and decision-makers’ reliabilities is developed. The proposed method is used to analyze a new business selection problem for an enterprise located in Changzhou, Jiangsu, China to demonstrate its applicability and validity.

Archimedean [formula omitted]-norm and [formula omitted]-conorm based intuitionistic fuzzy WASPAS method to evaluate health-care waste disposal alternatives with unknown weight information

Health-care waste (HCW) contains numerous hazardous, infectious, and radioactive contents that may cause serious health issues for society and drastic environmental problems. Therefore, it is crucial to dispose of HCW safely and appropriately. Four commonly used HCW disposal methods are incineration, steam sterilization, microwave, and landfill disposal. To select an appropriate HCW disposal method, there are several conflicting criteria. Furthermore, when information is lacking due to uncertainty and criteria weighing conditions are also unknown, the decision to choose an appropriate HCW disposal method becomes more challenging. So, the objective of this paper is to introduce a novel integrated multi-criteria group decision-making (MCGDM) approach to evaluate HCW disposal methods in which incomplete information is quantified using intuitionistic fuzzy sets (IFSs), unknown criteria weights are evaluated using the maximizing deviation method, and the evaluation of HCW disposal methods is done by applying the Archimedean t-norm and t-conorm-based interactive intuitionistic fuzzy weighted aggregated sum product assessment (WASPAS) method. Herein, the Archimedean t-norm and t-conorm cover a wide range of t-norms and t-conorms, including the Algebraic, Einstein, Hamacher, and Frank, etc., by adopting prescribed combinations of additive generators. The proposed MCGDM approach has been applied to evaluate the above-listed four HCW disposal methods for a case study conducted by Mishra et al. (2020) in the context of India. A sensitivity analysis is performed to examine the impact of changes in the parameters involved in the proposed MCGDM approach. A comparative study is also performed with some well-known multi-criteria decision making(MCDM) and MCGDM methods to demonstrate the consistency and stability of the proposed approach. Findings suggest that the newly developed MCGDM approach is more general, flexible, and provides realistic results to evaluate HCW disposal methods under uncertainty and unknown criteria weight information.

Toward Effective Uncertainty Management in Decision-Making Models Based on Type-2 Fuzzy TOPSIS

Over the past century, there has been a dramatic increasing interest in the multi-criteria group decision-making (MCGDM) technique, with a considerable amount of studies published regarding it. One of the well-known approaches in the MCGDM paradigm is Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The integration of the TOPSIS method with fuzzy set theory has proven to be successful in various applications. Recently, a wide array of publications has proposed implementing a type-2 fuzzy set with TOPSIS. However, the additional degree of uncertainty represented by type 2 has largely been ignored, especially in a few specific mathematical operations in the model. We propose constructing interval type-2 fuzzy membership functions (IT2 MFs) using interval-based data gathered from a survey, where this is used to generate a new scale to represent ratings for each alternative. This procedure utilized all information gathered from decision makers. In addition, we present a complete algorithm for TOPSIS based on IT2 fuzzy sets (IT2 FSs) which preserve the interval-based form output. The output in the form of intervals offers decision makers (DMs) with more detailed information, enabling them to make more nuanced decisions. This can include cautious decisions when intervals are wider and overlapping. Although understanding the exact meaning of these intervals and their widths in a decision-making context is challenging, this paper introduces a systematic method for connecting input uncertainty to output uncertainty in the TOPSIS technique. This approach establishes a solid foundation for future research. Thus far, no other researchers have suggested a data-driven method that combines TOPSIS with fuzzification and provides intervals as the final output.

A novel Aczel-Alsina triangular norm-based group decision-making approach under dual hesitant q-rung orthopair fuzzy context for parcel lockers’ location selection

For complex last mile problems, the parcel lockers play an important role in urban areas. So, selecting a suitable location is very much crucial to provide optimal service and better logistical performance. From that viewpoint, a multicriteria group decision making method is developed in this article using dual hesitant q-rung orthopair fuzzy (DHq-ROF) set which is more effective than existing variations of fuzzy sets. The Aczel-Alsina (AA) class of t-conorms and t-norms (AAt-CNs&t-Ns) emerged as an important class of union and intersection operations due to its greater flexibility in the information fusion process. To take advantage of the benefits of AAt-CNs&t-Ns and hybrid aggregation operators in DHq-ROF environments, several fundamental operations based on AAt-CNs&t-Ns are first defined. Following the introduction of these stated operations, a series of aggregation operators, viz., DHq-ROF AA weighted averaging, ordered weighted averaging, hybrid averaging and their geometric versions with DHq-ROF information, has been proposed. Based on these operators, a creative approach to handle multi-attribute group decision-making problems has been framed. The parcel lockers’ location selection problem is estimated to validate the created strategy and show its applicability and efficacy. The achieved results establish that the post office is the best location for locating parcel lockers.

A trust-based quantum probabilistic linguistic multi-criteria group decision making model considering interference effect

In group decision-making (GDM), there exist cognitive and realistic uncertainties and humans exhibit hesitation and ambiguity. Using probabilistic linguistic term sets (PLTSs) can better adapt to the above challenges. However, the current PLTS-based methods rarely take the subjectivity and behavior of experts into account, especially the influence of trust relations and subjective beliefs. This paper combines the trust network and the quantum probability theory (QPT) in GDM, and proposes a new probabilistic linguistic multi-criteria group decision-making (MCGDM) model considering the trust relationships and the interference effects between experts. Firstly, probabilistic linguistic evaluations and trust information are collected. Then, the entropy-weight method based on PLTS is proposed to determine criterion weights. A new mixed multi-path trust transfer aggregation operator that integrates both the path length and the path quality is defined, to establish a complete trust network and measure the expert weight. Thirdly, because of the certain interference between experts, a quantum-like Bayesian network framework is built to aggregate the opinions of experts. During the process, the system is in a superposition state, and personal opinions are regarded as interfering wave functions, affecting the final results. Finally, an example of the prevention and control of COVID-19 in a city is used for verification and sensitivity and comparison analyses are provided to verify the effectiveness of the method.