Multiple Attribute Group Decision-making Method Research Articles

Research on teaching quality evaluation of higher vocational architecture majors based on enterprise platform with spherical fuzzy MAGDM

Abstract Teaching quality evaluation is a process of evaluating the teaching quality of architectural majors. It can not only evaluate the teaching level of teachers, but also evaluate the learning effectiveness of students. Therefore, this study designs a teaching quality evaluation system for architecture majors based on fuzzy environment, in order to provide direction guidance for effectively evaluating the teaching quality of architecture majors by using this research. The teaching quality evaluation of higher vocational architecture majors based on enterprise platform is a multiple-attribute group decision-making (MAGDM). The spherical fuzzy sets (SFSs) provide more free space for decision makers to portray uncertain information during the teaching quality evaluation of higher vocational architecture majors based on enterprise platform. Therefore, this study expands the partitioned Maclaurin symmetric mean operator and induced ordered weighted average operator to SFSs based on the power average technique and construct induced spherical fuzzy power partitioned MSM (I-SFPPMSM) technique. Subsequently, a novel MAGDM method is put forward based on I-SFPPMSM technique and spherical fuzzy number weighted geometric technique under SFSs. Finally, a numerical example for teaching quality evaluation of higher vocational architecture majors based on enterprise platform is employed to verify the put forward method, and comparative analysis with some existing techniques to testy the validity and superiority of the I-SFPPMSM technique.

Advanced CoCoSo method for uncertain MAGDM: Evaluating college students’ entrepreneurial skills

With the in-depth implementation of the innovative development-driven strategy of “mass innovation and entrepreneurship” put forward by the state, colleges and universities, as the main positions for cultivating innovative and entrepreneurial talents, have set up a multi-level and all-round training system for college students’ innovative and entrepreneurial ability according to the relevant policies and implementation opinions of the state for deepening innovation and entrepreneurship education in colleges and universities, and actively promoted the improvement of college students’ innovative and entrepreneurial ability. The college students’ innovation and entrepreneurship ability evaluation could be regarded as the classical multiple attribute group decision making (MAGDM) issue. The PULTSs could well depict uncertain information during the college students’ innovation and entrepreneurship ability evaluation and the combined compromise solution (CoCoSo) method is appropriate to stable the decision-making results. In this paper, the probabilistic uncertain linguistic combined compromise solution (PUL-CoCoSo) method based on the probabilistic uncertain linguistic sets (PULTSs) and combined compromise solution method is proposed for multiple attribute group decision making (MAGDM). The weights of attribute based on the CRITIC method are obtained under PULTSs. Finally, an application related to the college students’ innovation and entrepreneurship ability evaluation is utilized to demonstrate the usage of the developed algorithms.

Multi-Attribute Group Decision-Making Problem Based On Q-Rung Orthopair Fuzzy Set Under Confidence Environment

Emergency decision-making for communities and countries is an important and critical tool. It improves the effectiveness and reliability to response emergencies which minimizes the rate of casualties, environmental damages and economic losses. In the event of emergency decision-making, the main issue is extreme imprecision, ambiguity, and fuzziness. This paper is devoted to the study of q‐rung orthopair fuzzy aggregation operators under the confidence levels and their applications to multiple-attribute group decision making (MAGDM) problems. The concept of q-rung orthopair fuzzy set (q-ROFS) is used as tool to describe undetermined information and is superior to the intuitionistic set (IFS) and Pythagorean fuzzy set (PFS). The distinguishing feature of the q-ROFS is that the sum of the q-th power of the membership degree and the q-th power of non-membership degree is bounded by 1. As a result, the range of uncertain information that it may describe is expanded. In this work, we focus on MAGDM problems under the fuzzy environment. First, based on aggregation operators some drawbacks of the already existing MAGDM methods are analyzed. Moreover, we present some modified operational laws and some of their properties to overcome these drawbacks. Next, related to q-ROFS fuzzy-weighted averaging (q-ICROFWA) and fuzzy-weighted power averaging (q-ICROFWPA) aggregation operator under confidence levels along with their properties are presented. By using these operators’ q-ICROFWA and q-ICROFWPA an advanced method is proposed to deal with MAGDM problems in fuzzy environment. At last, the validity and feasibility of this method is illustrated with some numerical examples.

Multi-Attribute Decision-Making Based on Picture Fuzzy Einstein Operator and The TOPSIS Method

Picture Fuzzy Sets (PFSs) denote the extension of conventional fuzzy sets, which capture a broader spectrum of human opinions, encompassing responses such as acceptance, neutrality, rejection, and hesitation. This wider range of responses cannot be accurately accommodated within fuzzy sets as well as intuitionistic fuzzy sets framework. In the realm of Multiple Attribute Group Decision-Making (MAGDM) methods, attributes frequently exhibit conflicts, uncertainties, imprecisions, as well as a lack of commensurability. To tackle the complexities inherent in MAGDM, the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) method has demonstrated its effectiveness. This method is employed in a compromise ranking approach founded on aggregation functions that showcase closeness to the reference points. This study's goal is to instigate a fresh approach to aggregation, referred to as the Picture Fuzzy Einstein Weighted Averaging Distance-based TOPSIS (PFEWAD-TOPSIS) method. To validate the effectiveness of this method in addressing MAGDM problems, a detailed example is conducted.

Enhanced CoCoSo method for picture 2-tuple linguistic MAGDM and applications to classroom teaching quality evaluation of college physical education

In order to better improve the physical health status of Chinese college students, enrich the knowledge content of university physical education courses, enhance their physical exercise ability, cultivate lifelong physical education awareness and conscious exercise habits, and promote the healthy development of quality education in China, combined with the current reality of university physical education teaching, a quality assurance system for university physical education teaching in China is constructed to promote the continuous improvement of the quality of university physical education teaching. The guarantee system for college physical education teaching consists of three subsystems: the design and quality management system for college physical education teaching objectives, the evaluation system for college physical education teaching quality, and the feedback system for college physical education teaching quality information. The quality evaluation of college physical education classroom teaching is a multiple attribute group decision making (MAGDM) issue. In this paper, depending on the CoCoSo (Combined Compromise Solution) method and picture 2-tuple linguistic sets (P2TLSs), a novel MAGDM issue based on the picture 2-tuple linguistic CoCoSo (P2TL-CoCoSo) method is designed to tackle it. In addition, the weights of criteria are decided objectively by utilizing entropy method. Eventually, a related application for quality evaluation of college physical education classroom teaching and comparative analysis is given to demonstrate the superiority of the designed method. The results illustrate that the designed method is useful for quality evaluation of college physical education classroom teaching.

Framework for service quality evaluation of international logistics enterprises from the perspective of cross-border e-commerce supply chain under spherical fuzzy sets

With the rapid development and application of internet technology, cross-border e-commerce (CBEC) has begun to popularize globally and play an important role in China’s foreign trade. The Chinese government has successively introduced multiple policies and regulations to strongly support its rapid development. Compared to the booming trend of CBEC, the development of its supply chain is slightly lacking in momentum, which has formed a certain obstacle to the overall development of CBEC. The supply chain is the foundation of successful CBEC transactions, and the foundation of the supply chain is logistics. The primary task to improve the backwardness of supply chain development is to solve logistics problems. Therefore, while enjoying the dividends brought by the rapid development of CBEC, international logistics enterprises should continuously improve their logistics service capabilities, effectively evaluate their service quality, and then identify problems based on the evaluation results, analyze and improve them. The service quality evaluation of international logistics enterprises from the perspective of CBEC supply chain is a classical multiple attribute group decision making (MAGDM). The Spherical fuzzy sets (SFSs) provide more free space for DMs to portray uncertain information during the service quality evaluation of international logistics enterprises from the perspective of CBEC supply chain. Therefore, this paper expands the partitioned Maclaurin symmetric mean (PPMSM) operator and IOWA operator to SFSs based on the power average (PA) technique and construct induced spherical fuzzy weighted power partitioned MSM (I-SFWPPMSM) technique. Subsequently, a novel MAGDM method is constructed based on I-SFWPPMSM technique and SFNWG technique under SFSs. Finally, a numerical example for service quality evaluation of international logistics enterprises from the perspective of CBEC supply chain is employed to verify the constructed method, and comparative analysis with some existing techniques to testy the validity and superiority of the I-SFWPPMSM technique.

An ExpTODIM-GRA based multiple attribute group decision-making method for development level evaluation of digital inclusive finance under intuitionistic fuzzy circumstances

In recent years, due to the rapid development of internet technology, the integration process of digital technology and financial services has accelerated. Digital Financial inclusion has emerged as the times require, becoming an important force to promote private enterprises to get out of financing difficulties. The development level evaluation of digital inclusive finance is a classical multiple attribute group decision making (MAGDM) problems. Recently, Recently, the Exponential TODIM(ExpTODIM) and (grey relational analysis) GRA method has been used to cope with MAGDM issues. The intuitionistic fuzzy sets (IFSs) are used as a tool for characterizing uncertain information during the development level evaluation of digital inclusive finance. In this paper, the intuitionistic fuzzy Exponential TODIM-GRA (IF-ExpTODIM-GRA) method is built to solve the MAGDM under IFSs. In the end, a numerical case study for development level evaluation of digital inclusive finance is supplied to validate the proposed method. The main contributions of this paper are outlined: (1) the ExpTODIM and GRA method has been extended to IFSs; (2) Information Entropy is used to derive weight under IFSs. (3) the IF-ExpTODIM-GRA method is founded to solve the MAGDM under IFSs; (4) a numerical case study for development level evaluation of digital inclusive finance and some comparative analysis are supplied to validate the proposed method.

A novel group decision making model based on Interval neutrosophic sets for product modeling design quality evaluation

The energy consumption of mechanical products in China is enormous, and the energy utilization rate is low, which is increasingly receiving people’s attention. Conducting product design for energy optimization is of great significance for improving energy utilization efficiency. The scheme design of a product is the key to achieving innovation in product design, and the evaluation and decision-making of the design scheme directly affect the results of the later stage of the design. Therefore, correctly evaluating and making reliable decisions on product design schemes that are oriented towards fuzzy decision optimization is an important aspect of product innovation conceptual design. The product modeling design quality evaluation is a multiple attribute group decision making (MAGDM) problems. Recently, the Combined Compromise Solution (CoCoSo) method and information entropy method has been employed to cope with MAGDM issues. The interval neutrosophic sets (INSs) are employed as a tool for portraying uncertain information during the product modeling design quality evaluation. In this paper, the CoCoSo method is designed for MAGDM under INSs. Then, the interval neutrosophic numbers CoCoSo (INN-CoCoSo) method based on the Hamming distance and Euclidean distance is built for MAGDM. The information Entropy method is employed to produce the weight information based on the Hamming distance and Euclidean distance under INNSs. Finally, a practical numerical example for product modeling design quality evaluation is supplied to show the INN-CoCoSo method. The main contributions of this paper are constructed: (1) This paper builds the novel MAGDM based on CoCoSo model under INSs; (2) The information Entropy method is employed to produce the weight information based on the Hamming distance and Euclidean distance under INNSs; (3) The new MAGDM method is proposed for product modeling design quality evaluation based on INN-CoCoSo.

Integrated MAGDM framework based on spherical fuzzy sets for teaching quality evaluation of ideological and political courses in universities

With the rapid development of society, ideological and political education courses have occupied a very important position in various courses in major universities, playing a series of important functions and roles in student quality education, excellent quality cultivation, and other aspects. In the new era, the evaluation and assessment of ideological and political education quality is not only the primary factor to improve the teaching quality of ideological and political education courses in universities, but also an important means to promote the deepening reform of ideological and political education. However, there are many problems in the process of evaluating the quality of ideological and political education in colleges and universities at present, such as the deviation in understanding the importance of evaluation, the relatively single evaluation method, and the low quality of application of evaluation results. The teaching quality evaluation of ideological and political courses in universities is a classical multiple attribute group decision making (MAGDM). Spherical fuzzy sets (SFSs) provide more free space for decision makers (DMs) to express preference information during the teaching quality evaluation of ideological and political courses in universities. Therefore, this paper we first extend partitioned Maclaurin symmetric mean (PMSM) operator and IOWA operator to SFSs and develop induced spherical fuzzy weighted PMSM (I-SFWPMSM) operator. Subsequently, a new MAGDM method is established based on I-SFWPMSM operator and SFNWG operator under SFSs. Finally, a numerical example for teaching quality evaluation of ideological and political courses in universities is used to illustrate the proposed method.

CODAS method for Pythagorean 2-tuple linguistic MAGDM and applications to quality evaluation of scientific research management in application-oriented universities

The scientific research work of colleges and universities has attracted more and more social attention because of its large number of multidisciplinary scientific and technological talents, hardware facilities and good scientific research environment, and the quality of scientific and technological management work of colleges and universities directly affects the level of scientific and technological work of colleges and universities. Starting from the common problems of scientific research management in colleges and universities, this paper explores the ideas and methods to further promote scientific research work by improving the quality of scientific research management. The quality evaluation of scientific research management in application-oriented universities is classical multiple attribute group decision making (MAGDM). Based on this, we extend the traditional CODAS method to the Pythagorean 2-tuple linguistic sets (P2TLSs) and propose the Pythagorean 2-tuple linguistic CODAS (P2TL-CODAS) method for quality evaluation of scientific research management in application-oriented universities. The P2TL-CODAS method is established and all computing steps are simply presented. Furthermore, we apply the P2TL-CODAS method to evaluate the quality evaluation of scientific research management in application-oriented universities.

Extended QUALIFLEX method for MAGDM under Picture 2-Tuple Linguistic environment and applications to college English classroom teaching quality evaluation

With the globalization of the world’s economy, culture, science and technology, and the increasing frequency of international cooperation and exchanges, English will play an increasingly important role. For non-English majors in Chinese colleges and universities, college English is a public compulsory basic course, which plays a very important role in expanding students’ knowledge, improving foreign language cultural literacy and comprehensive language use ability. An important part of college English classroom teaching is teaching evaluation, which not only helps teachers obtain teaching feedback information, improve teaching management, and ensure teaching quality, but also effectively helps students adjust learning strategies, improve learning methods, and improve learning efficiency. The English classroom teaching quality evaluation could be deemed as a classic multiple attribute group decision making (MAGDM) problem. In this paper, as a useful outranking approach, the extended QUALIFLEX method is utilized to address some MAGDM issues by using picture 2-tuple linguistic sets (P2TLSs). In addition, integrating the QUALIFLEX method with P2TLSs, the extended QUALIFLEX method with P2TLNs is constructed and all calculating procedures are simply depicted. Eventually, an empirical application of English classroom teaching quality evaluation has been offered to demonstrate this novel method.

Extended QUALIFLEX method for electronic music acoustic quality evaluation based on the picture fuzzy multiple attribute group decision making

In the past, different useful extensions of fuzzy sets were established by the researchers to manage the vagueness and uncertainty in various practical problems. Usually, the real numbers are utilized to express the decision information, but it is noted that the description of attributes using picture fuzzy sets (PFSs) proves to be more appropriate. As a powerful decision tool, PFSs provides more decision information that requires the application of some specific situations more types of response of human ideas: yes, contain, no, reject. QUALIFLEX (qualitative flexible multiple criteria method), is one of the well-known outranking methods to solve the multiple attribute group decision making (MAGDM) problems with crisp numbers. The QUALIFLEX method can perfectly address the complex MAGDM problems where a lot of attributes are utilized to assess a limited number of alternatives. The electronic music acoustic quality evaluation is a classical MAGDM. This paper proposes and utilizes the QUALIFLEX to develop the picture fuzzy QUALIFLEX(PF-QUALIFLEX) method for MAGDM. The current study is mainly devoted to explore and extend the measurement of alternatives and ranking according to the QUALIFLEX under the background of PFSs. Furthermore, an example to evaluate the electronic music acoustic quality is handled through the proposed method to substantiate the extended approach.

Method for 2-tuple linguistic neutrosophic number MAGDM and applications to physical education teaching quality evaluation in colleges and universities

The quality of physical education (PE) teaching in colleges and universities is the basis for the development of PE disciplines in colleges and universities, so currently thinking about how to effectively improve the quality of PE teaching in colleges and universities has become the first and foremost problem for many college and university PE departments to solve. In order to solve this problem, it is necessary to build a reasonable and scientific evaluation and monitoring system of PE teaching quality, because only by establishing an effective evaluation and monitoring system of teaching quality can we evaluate and supervise all the PE operation properly and scientifically, and then give feedback in the process of evaluation and supervision, such evaluation and monitoring system can greatly promote the continuous improvement of PE teaching quality in colleges and universities. This is also one of the most effective means to improve the quality of PE and achieve the goal of PE in colleges and universities. The PE teaching quality evaluation in Colleges and Universities is frequently viewed as the multiple attribute group decision making (MAGDM) issue. In this paper, the 2-tuple linguistic neutrosophic number grey relational analysis (2TLNN-GRA) method is built based on the traditional grey relational analysis (GRA) and 2-tuple linguistic neutrosophic sets (2TLNNSs). Then, a numerical example for PE teaching quality evaluation in Colleges and Universities has been given and some comparisons is used to illustrate advantages of 2TLNN-GRA method.

Model-based evaluation for online food delivery platforms with the probabilistic double hierarchy linguistic EDAS method

In recent years, with the rapid expansion of internet technology, the number of online food delivery services has grown. Despite the ease, a poor online food delivery platform (OFP) produces all kinds of problems for individuals. A comprehensive and reasonable evaluation of online food delivery is of great significance. Therefore, this study establishes an OFP evaluation model based on the probabilistic double hierarchy linguistic EDAS (PDHL-EDAS) method for multiple attribute group decision-making (MAGDM). Then the CRITIC model is introduced to derive the objective weight and the cumulative prospect theory is leaded to obtaining the cumulative weight of PDHLTS. In furthermore, the benefits and applicability of the PDHL-EDAS method are illustrated by solving practical MAGDM problems concerning the evaluation of OFPs. Lastly, the proposed method is verified by comparison with other MAGDM methods, in addition to discussing potential future research directions.

How do enterprises determine which breakthrough invention should be commercialized? A multiple attribute group decision-making-based method

The problem of selection of breakthrough inventions to be commercialized (SBIC) is significantly important for innovative enterprises. As the processes of commercializing breakthrough inventions are time-consuming and high-cost, enterprises have to tradeoff among all possible inventions and determine which inventions should be commercialized. SBIC refers to a process in which multiple experts are invited to evaluate the potential of all inventions from multiple aspects and based on their assessments, the breakthrough inventions to be commercialized are chosen. Hence, the essence of SBIC is consistent with multiple attribute group decision-making (MAGDM). This paper proposes a MAGDM-based model to help enterprises conduct SBIC. In our model, probabilistic dual Pythagorean hesitant fuzzy sets (PDPHFSs) are utilized to represent DMs’ evaluation information, which can express DMs’ evaluation information comprehensively. Then, an attributes’ weights determination method is proposed to handle MAGDM with unknown weights information. Afterwards, we extend the classical projection model into PDPHFSs and introduce a novel MAGDM method and its detailed calculation process is illustrated. Finally, our MAGDM method is applied to an SBIC problem to show its effectiveness. Comparison analysis is conducted to show the advantages of our method.

A TWO-STAGE MATHEMATICAL PROGRAMMING MODEL FOR DISTRIBUTED PHOTOVOLTAIC PROJECT PORTFOLIO SELECTION WITH INCOMPLETE PREFERENCE INFORMATION

With the rapid growth of the solar photovoltaic (PV) market, many distributed PV power projects are introduced to the market. Selecting a rational project investment portfolio is a complex and challenging task for energy enterprises as both financial and non-financial factors of projects are needed to be considered under limited information and resources. This study presents a two-stage hybrid multi-attribute decision-making and integer programming model for distributed PV project portfolio selection. In Stage I, a multiple attribute group decision-making method based on mathematical programming is used to evaluate the non-financial value of projects under incomplete preference information. Compensative weighted averaging operators with an adjustable parameter are utilized to capture the subjective attitudinal character of an expert in the aggregation process. Then, a rank acceptability index is developed to measure each project’s group support degree in non-financial dimension. In Stage II, a bi-objective integer programming model is constructed to optimize project portfolios, which considers both financial and non-financial values of projects under resource, carbon emission and other strategic constraints. The applicability and effectivity of the proposed approach are demonstrated by a case study of a distributed PV project portfolio selection.

A dynamic large-scale multiple attribute group decision-making method with probabilistic linguistic term sets based on trust relationship and opinion correlation

Dynamic large-scale multiple attribute group decision making (DLMAGDM) is ubiquitous in many areas of the real world. It is composed of large numbers of decision makers, several continuous periods, alternative set and attribute set changed with time. Given the characteristics implicited in decision-making elements and the advantages of probabilistic linguistic term sets (PLTSs) in modelling uncertainty and complexity of decision makers’ subjective opinions, this paper constructs a probabilistic linguistic DLMAGDM method. First of all, a dynamic weight determination model based on trust relationships and evidential conflicts between decision makers is proposed to obtain current dynamic weights of decision makers. Then, a comprehensive hierarchical clustering method that divides large numbers of decision makers into several subgroups is constructed based on three clustering constrains. Moreover, some probabilistic linguistic extended evidential power aggregation operators are proposed to aggregate PLTSs. These operators can appropriately handle the extreme PLTSs and fully consider the role of incomplete probabilistic distributions in PLTSs. In addition, a dynamic decision-making method based on PROMETHEE is developed to determine the final priority order of alternatives according to preferences between alternatives over several periods. Lastly, a case study for supply chain finance risk assessment for several firms in Chinese household appliance industry is utilized to illustrate the practicality and effectiveness of the probabilistic linguistic DLMAGDM method. Furthermore, the comparative analysis with some other existing methods and the sensitivity analysis are made to verify its advantages.

Robot Selection Using An Integrated MAGDM Model Based on ELECTRE Method and Linguistic q-Rung Orthopair Fuzzy Information

With the development of engineering sciences, many companies are using robots in different industries to improve the efficiency and accuracy of their work. However, the need for robots under different requirements is different, which makes the selection of robots complex. In this paper, a linguistic q-rung orthogonal fuzzy multiple attribute group decision-making (MAGDM) method based on ELECTRE is proposed for robot selection. First, the basic Hausdorff distance is extended to the linguistic q-rung orthopair fuzzy environment to measure the deviation between two linguistic q-rung orthopair fuzzy numbers and two linguistic q-rung orthopair fuzzy sets. Then, the properties of the linguistic q-rung orthopair fuzzy distance measure based on Hausdorff distance are investigated. In addition, two maximum deviation models for deriving the weights of decision-makers and attributes are proposed. Moreover, a new MAGDM method is proposed by extending the ELECTRE method to the linguistic q-rung orthopair fuzzy environment. Finally, the practicality as well as the effectiveness of the method is demonstrated through a case study of the robot selection problem. The linguistic q-rung distance measure is used to construct two maximum deviation models to objectively derive the weights of attributes and decision-makers, and the linguistic q-rung orthopair fuzzy ELECTRE method is used to complete the selection of robots for a clean energy company. Furthermore, the sensitivity analysis of the parameter in the proposed method is provided, and the superiority of the new method is illustrated by the comparison with existing MAGDM methods.

An integrated hesitant fuzzy linguistic model for multiple attribute group decision-making for health management center selection

Eliciting information in multiple attribute group decision-making (MAGDM) is a key for obtaining more reliable results in decisions defined under uncertain domains. In this case, the use of a hesitant fuzzy linguistic term set (HFLTS) as a flexible model to express decision-makers’ (DMs’) qualitative and hesitant decision-making information has been successfully applied to multiple decision situations. However, in many decision situations, DMs’ and attributes’ weights are still subjectively provided. These actions may cause randomness of decision results. Therefore, to solve the two issues, this paper aims to develop a group consensus optimization model and DEA (data envelopment analysis) model to derive DMs’ weights and attributes’ weights, respectively, based on HFLTS. Hence, a new hesitant fuzzy linguistic distance measure is introduced first, and some properties are discussed. The individual consensus measure and the group consensus measure are then defined based on this hesitant fuzzy linguistic distance measure. Subsequently, a new group consensus optimization model is introduced and included in the DEA-based TODIM method for MAGDM with HFLTSs. This integrated approach is applied in health management center site selection. Finally, a sensitivity and a comparative analysis with other methods such as hesitant fuzzy linguistic VIKOR and hesitant fuzzy linguistic TOPSIS are performed to show the validity of our proposed approach.

An extended MABAC method for multiple-attribute group decision making under probabilistic T-spherical hesitant fuzzy environment

PurposeThe purpose of this article is to present the idea of a T-spherical hesitant fuzzy set associated with probability and to develop an extended multi-attributive border approximation area comparison (MABAC) method under probabilistic T-spherical hesitant fuzzy (Pt-SHF) settings.Design/methodology/approachThe authors define some basic operational laws for Pt-SHF sets (Pt-SHFSs) and a comparison method of two probabilistic T-spherical hesitant fuzzy numbers (Pt-SHFNs) is proposed. Moreover, some Pt-SHF aggregation operators and the multi-attributive border approximation area comparison (MABAC) method are established under Pt-SHF scenario to solve group decision making problems.FindingsThe developed Pt-SHF MABAC method for multi-attribute group decision making (MAGDM) can overcome the drawbacks of conventional MABAC method and limitations for decision makers, which they face while providing their assessment concerning any object.Research limitations/implicationsClearly, this paper is devoted to MABAC method, MAGDM and probabilistic T-spherical hesitant fuzzy set theory.Practical implicationsThe approach established can be used in a variety of scenarios, including decision making, engineering, and economics. An explanatory example is illustrated which shows the superiority and effectiveness of our proposed technique.Originality/valueIf a T-spherical fuzzy MAGDM problem under the probabilistic scenario needs to be evaluated, the involvement of probabilities in fuzzy system will be lost because of no information. This work fills a gap in literature by establishing the notion of probabilistic t-spherical hesitant fuzzy set to deal with the ambiguity, uncertainty in decision making problems.