Multi-criteria Group Decision Research Articles

Multicriteria group decision making for prioritizing IoT risk factors with linear diophantine fuzzy sets and MARCOS method

In a dynamic world of technological advances, the Internet of Things (IoT) is a transformational and widespread force that has revolutionized the way we communicate with our surroundings and regulate our environments. It offers several advantages but also introduces inherent risks. In this study, we provide a comprehensive analysis of the risks associated with IoT and employ the effectiveness of a Linear Diophantine Fuzzy Set to rank the risk factors. Because of the significant uncertainties frequently present in IoT contexts, the use of a fuzzy framework is invaluable in discerning and addressing these risks. The primary contribution is to employ the Measurement of Alternatives and Ranking according to the Compromise Solution (MARCOS) method and linear diophantine fuzzy sets to propose a multi-criteria group decision-making method (MCGDM) for ranking attributes to facilitate risk prioritization, enabling consumers to determine the crucial hazards in their IoT systems. Furthermore, we implement a comparative study and a sensitivity analysis to demonstrate the robustness of our proposed methodology. The insights obtained from our research not only improve the awareness of IoT hazards but also enable organizations and individuals to make informed decisions when navigating IoT fields. By proactively addressing these risks, we endorse the development and secure deployment of IoT technology.

Multi-criteria group decision making through full multiplicative form under hesitant Fermatean fuzzy environment

Multi-criteria group decision making through full multiplicative form under hesitant Fermatean fuzzy environment

Picture Fuzzy Aggregation Operator-Based Integrated MEREC-WASPAS Technique for Video Conferencing Tool Selection

The COVID-19 epidemic has drastically altered the global landscape and thus organizations are finding it difficult to provide a modern and productive work environment to their stakeholders. As a result, personnel have shifted from in-person interactions to working remotely via video conferencing tools (VCTs). Owing to the onset of COVID-19 outbreak, usage of VTCs has gained great interest among people, especially student fraternity and employees as it reduces the hassle of direct interaction. But selecting the right platform for virtual interaction can be challenging, as it involves a number of factors in order to reduce expenses and maximize productivity. The present treatise has focused on devising a mathematical approach to identify the best VCT by structurizing the problem as a multi-criteria group decision making (MCGDM) model. To carry out the research, the notions of two popular techniques, namely Method based on the Removal Effects of Criteria (MEREC) and Weighted Aggregated Sum Product Assessment (WASPAS) have been extended under Picture fuzzy environment with the aid of Picture fuzzy weighted averaging operator to deal with MCGDM situation. Furthermore, to overcome limitations of existing Picture fuzzy score function (PFSF), a novel PFSF has been developed and its significant properties are analyzed through theoretical and numerical justifications, showing its superiority over the existing one. The proposed PFSF can not only overcome the limitations of the existing SF, but also can rank any type of Picture fuzzy numbers irrespective of their membership and non-membership grades. Thereafter, the extended MCGDM techniques have been integrated with the aid of the proposed novel PFSF and applied to assess the best VCT. The proposed technique has identified Google Meet as the best VCT for virtual communication. Consistency and robustness of proposed technique have been validated through comparative and sensitivity analysis.

“Multi-Criteria Group Decision Making Approach for Scheduling Algorithms Selection by Short Term Scheduler using Fuzzy TOPSIS”.

The fundamental objective of the CPU scheduler is to equitably and effectively allocate CPU time among competing processes. Within the realm of schedulers, the short-term scheduler specifically addresses this objective by selecting processes from the ready queue for execution on the CPU, guided by various scheduling algorithms. The critical challenge faced by the short-term scheduler lies in the prudent selection of the most suitable algorithm, as an erroneous choice can detrimentally impact system performance, leading to increased waiting and response times for processes. To surmount this challenge, we employ the Fuzzy TOPSIS method within the framework of Multi-Criteria Decision Making (MCDM) to rank scheduling algorithms, taking into account both quantitative and qualitative factors. The proposed approach involves two steps: firstly, defining criteria for algorithm selection, and secondly, obtaining linguistic ratings from experts for potential alternatives based on the specified criteria. The principal aim of this investigation is to utilize the Fuzzy TOPSIS method, integrating fuzzy sets, to produce comprehensive scores that assist in selecting the optimal alternative.

A hybrid multi-criteria group decision methodology based on fairly operators and EDAS method under interval-valued Fermatean fuzzy environment

A hybrid multi-criteria group decision methodology based on fairly operators and EDAS method under interval-valued Fermatean fuzzy environment

Ranking of asset maintenance process KPIs using Fermatean fuzzy Delphi and Fermatean fuzzy ELECTRE method

The paper aims to present a hybrid model for measuring the performance of business processes in complex organizations based on the subjective decision-making of expert teams. The subject of the research is finding ways to measure, analyze and improve the key performance indicators (KPIs) process. Obtaining the values of KPIs, which reflect the real state of the process, creates a basis for their ranking, i.e. insight into KPIs that are extremely important for the process as well as KPIs that are of lesser importance, but as such are not excluded from consideration because they are necessary for the beginning, realization and completion of the process. The model was compiled through five phases and was tested through a case study in a real business organization, which deals with the maintenance of complex combat systems. The obtained results helped the management to take certain measures in order to improve the performance of the maintenance process. In the model, it is proposed to form two expert teams, which make assessments based on experience and express them in linguistic terms according to a predefined scale. Modeling of linguistic expressions is realized using intuitive fuzzy sets of a higher order, more precisely Fermatean fuzzy sets (FFS). Selecting KPIs, decomposing the process into sub-processes and assessing the relative importance of sub-processes is carried out by one team of experts, while another team carries out the assessment of KPIs at the level of each sub-process. Determining the relative importance of sub-processes is realized using the Delphi method extended to FFS while reaching a consensus. The measurement of process performance, i.e. the value of KPIs, is realized using Multi-Criteria Group Decision-Making (MCGDM), such as the ELECTRE method extended with FFS. The sensitivity analysis of the developed model is realized by uncertainty modeling with q-rung orthopair fuzzy sets.

Some new open sets in bipolar N-neutrosophic supra topological spaces

The primary focus of this work is to develop the concept of bipolar N-neutrosophic supra topological spaces. Also, extended some concepts such as closure and interior operators of N-neutrosophic supra topological spaces to Bipolar N-neutrosophic supra topological spaces. The properties and relationship between weak forms of bipolar N-neutrosophic supra topological open sets are also established. Further, suggested several separations amongst bipolar N-neutrosophic supra sets. Some distance between bipolar N-neutrosophic sets is introduced and an efficient approachfor group multi-criteria decision making based on bipolar N-neutrosophic sets is proposed.

Group decision support system based on multi-granular fractional orthotriple fuzzy 2-tuple linguistic information model

The aim of this work is to put forward the concept of a novel decision support model for multi-criteria group decision making problems with multi-granular fractional orthotriple fuzzy 2-tuple linguistic (FOF2TL) information. The idea of fractional orthotriple fuzzy 2-tuple linguistic (2TL) model is put forward by integrating the advantages of fractional orthotriple fuzzy set and 2-tuple linguistic method. We define a transformation function to deal the consistency of multi-granular FOF2TL information. Secondly, the Archimedean coupla as well as the co-coupla are used to define operational laws for fractional orthotriple fuzzy 2-tuple linguistic numbers (FOF2TLNs). We take the relationship between attribute and experts, and defined fractional orthotriple fuzzy 2-tuple linguistic Banzhaf Choquet-Copula aggregation (FOF2TLBCCA) operators. Third, a method explains how to determine the fuzzy measure of expert and attribute sets. Next, the suggested operators are used to develop associated decision-making approaches. Finally, a numerical case is offered to demonstrate the concept's usefulness, along with pertinent comments; the merits of the suggested methodology are also evaluated by comparing it to several existing decision approaches.

Double-layer multi-criteria group decision-making approach using neutralized possibility degree-based decision matrix with fuzzy information

Multi-criteria group decision-making (MCGDM) problems are fundamentally characterized by uncertainty and ambiguity. The quantification of such data is vital for determining the most optimal course of action. In this paper, a double-layer possibility degree-based interval-valued q-rung orthopair fuzzy sets (IVq-ROFSs) Vlsekriterijumska Optimizacija i Kompromisno Resenje (VIKOR) approach is presented. First, the possibility degrees of IVq-ROFSs are calculated and processed to establish a new neutralized decision matrix. Second, the components of the new decision matrix are taken into account for obtaining a new pair of positive and negative ideal solutions. The utility and regret measures in the VIKOR approach are ultimately determined by combining criteria weights and cumulative possibility degrees to rank the alternatives. The results of the study show that the proposed approach contributes to acquiring accurate alternative rankings in situations where traditional approaches have had difficulty generating ranks. Also, by eliminating the early normalization stage, which has a direct impact on the final ranking, the proposed approach concludes a unique ranking for each decision-making problem. Several comparative and sensitivity analysis are also conducted to exhibit robustness and applicability of the proposed approach in real world.

Enhanced MAIRCA technique for green supply chain management based on spherical linear diophantine fuzzy information

Spherical q-linear Diophantine fuzzy sets (Sq-LDFSs) showed a significant improvement to handling uncertainty in multi-criteria decision-making (MADM). It is advantageous for two-parametric data as well as for data with three variable parameters. One of the most crucial functions of supply chain management is to increase competitive pressure. The study’s standout innovation, Multi-Attributive Ideal Real Comparative Analysis (MAIRCA), has been implemented to give powerful group decision-making. An ecological perspective is becoming more prevalent due to the competitive climate and customer perception. Green supplier selection (GSS) has become a significant issue. In this study, we address the problem of GSS, which aims for flexibility, robustness, ecological sensitivity, leanness, and feasibility. The feasibility criteria in recycling, environmental, carbon footprints, and water consumption are different from those in standard supplier selection. The aim of our work is to introduced the weighted Average/Geometric aggregation operators based on Sq-LDFSs. For this we defined some operational rules as a foundation of aggregation operators. Secondly we proposed a MAIRCA approach for Sq-LDFSs to address these issues. The MAIRCA strategy, which uses multi-criteria group decision-making (MCGDM) to evaluate and choose traditional and environmental conventionalities, is used to reduce instability and ambiguity. The spherical q-linear Diophantine fuzzy MAIRCA approach provides comparative analysis of decision-makers and criteria. By merging Sq-LDFS and MAIRCA, a hybrid strategy is formed, successfully selecting the best provider among options based on the order of significance. These numerical examples demonstrate the suggested MCGDM approaches that were applied in actual situations, giving a realistic appreciation of their efficacy. The comparative study of the final ranking further supports the idea that these strategies are dependable in decision-making processes in addition to being practical and usable.

An integrated multi-polar fuzzy N-soft preference ranking organization method for enrichment of evaluations of the digitization of global economy

Digitization represents the ultimate expression of globalization that has revolutionized every facet of global existence, enhancing connectivity, financial terms, trade opportunities, and public services. To further broaden or fortify this digital realm and advance global progress, various strategies for multi-criteria group decision-making (MCGDM) have been developed. This research article extends the literature study on the sensational MCGDM method known as Preference Ranking Organization Method for Enrichment of Evaluations (PROMETHEE), which shares the burden of selecting the best alternative under many terms and conditions. This article aims to make a positive contribution to the development of the digital world. The main principle of the PROMETHEE technique is to calculate positive and negative flows of the selected options according to the divergence of the alternatives’ scores. It provides us with partial and full rankings of options by determining score degrees, suitable preference functions, and a multi-criteria preference index. To deal with the multi-polarity of the modern world and assign N-ordered levels, this paper proposes the multi-polar fuzzy N-soft (mFNS) PROMETHEE technique. Prior to this, an Analytic Hierarchy Process (AHP) technique is applied to guarantee the credibility of the criterion weights for each criterion. After that, the whole strategy of m-polar fuzzy N-soft PROMETHEE approach to order the selected options is explained, and all the course of action of this remarkable (MCGDM) technique are synchronized in an extensive flowchart, helping us to learn more about the technology keenly. Moreover, the utility of our discussed technology is illustrated by considering two applications of generating electricity through human movement and choosing the best digital currency. The most suitable choice is extracted with the help of the outranked directed graph. The results obtained by mFNS PROMETHEE technique benefits us with the selection of most reliable source to digitized the global economy, in addition, It enables us to rank the alternatives from most preferable to least one, that not only saves time but also produces the better outcomes. Subsequently, the eminence of mFNS PROMETHEE technology is checked by comparability with the prior art. Lastly, the advantages and disadvantages of our proposed technique are supplemented to demonstrate its productivity and shortcomings.

A multi-criteria group decision-making method based on consistency of interval-valued distributed preference relations

In multi-criteria group decision making (MCGDM) with interval-valued distributed preference relations (IDPRs), the consistency of IDPRs is important to guarantee the rationality of IDPRs and the rationality of group-satisfactory solutions. In existing studies, the consistency of the score intervals of IDPRs was considered to ensure the consistency of IDPRs. Meanwhile, a comparison of the score intervals of IDPRs was considered to approximately compare the IDPRs. The transformation from IDPRs into score intervals involved in the consistency and comparison of IDPRs results in information loss and unexpected group solutions. To avoid the influence of information loss on the group solutions, this study proposes an MCGDM method based on the consistency of IDPRs. Six transitive rules were constructed and used to define the distributed transitivity of IDPRs, which differs from existing types of consistency because IDPRs are on a set of discrete grades. With the grade scores, an abstract function with two variables was defined, in which ten conditions were satisfied. Using an abstract function with the scores of the two grades as two parameters, the mechanism of combining the two grades in the two IDPRs was designed by following the principles of mutual independence and probabilistic operation. The consistency of IDPRs is then constructed based on the combination mechanism, which is theoretically proven to satisfy distributed transitivity. In addition, the mean of the odd-order origin moment intervals of an IDPR was used to compare the alternatives. Information loss was avoided from two perspectives. The ultrasonic machine supplier selection problem of a tertiary hospital located in Hefei, Anhui, China was solved using the proposed method to demonstrate its applicability and effectiveness.

Confidence Picture fuzzy hybrid aggregation operators and its application in multi criteria group decision making

Confidence Picture fuzzy hybrid aggregation operators and its application in multi criteria group decision making

An approach of multi-criteria group decision making with incomplete information based on formal concept analysis and rough set

Decision-making problem is a fundamental activity in human life every day. Regarding group decision-making, individuals have insufficient comprehension of the decision objects owing to the limited experience and knowledge and drawback the evaluation process. Therefore, the evaluation information is missing and the group cannot get the precise information for decision objects resulting in the generation of incomplete information systems. It is meaningful for individuals finding an approach to Leverage and tap into existing information. On the basis, the work presented in this paper focuses on group decision-making problems (GDM) with incomplete information. Under the framework of group decision-making, a GDM approach with an incomplete information system is presented combining the formal concept analysis and rough set theory. Firstly, we propose a concept called formal decision context and discuss the properties of the formal decision context, which could divide the incomplete information system into many cognitive units, and the definitions of cognitive units will be given. Then, the property and the relations of various cognitive units will be discussed. Additionally, the upper and lower approximation space under the formal decision context is founded considering the risk attitudes integrating fuzzy rough set and formal concept context. Considering the order relation of various cognitive units and decision objects, we introduce the dominance relation and the importance degree of each cognitive unit under the framework of formal decision context. Furthermore, a theoretical framework of the multi-criteria decision-making problem is presented and two models for the multi-criteria group decision-making problem are discussed combined with fuzzy rough set and formal decision context from two perspectives, including qualitative analysis and quantitative analysis. Finally, an illustrated example is applied to verify the validity and effectiveness of the proposed models. The contributions of this paper include two aspects. On the one hand, this paper provides a new perspective and paradigm considering MCGDM problems with the incomplete information system from the perspective of group consensus. On the other hand, this paper gives two approaches for group decision-making problems from sorting and set theory by the perspective of multi-granular rough set and group consensus.

Novel Multi-Criteria Group Decision Making Method for Production Scheduling Based on Group AHP and Cloud Model Enhanced TOPSIS

Optimized production scheduling can greatly improve efficiency and reduce waste in the steel manufacturing industry. With the increasing demands on the economy, the environment, and society, more and more factors need to be considered in the production scheduling process. Currently, only a few methods are developed for the comprehensive evaluation and prioritization of scheduling schemes. This paper proposes a novel MCGDM (multi-criteria group decision making) method for the ranking and selection of production scheduling schemes. First, a novel indicator system involving both qualitative and quantitative indicators is put forward. Diverse statistical methods and evaluation functions are proposed for the evaluation of quantitative indicators. The evaluation method of qualitative indicators is proposed based on heterogeneous data, cloud model theory, and group decision-making techniques. Then, a novel Group AHP model is proposed to determine the weights of all evaluation indicators. Finally, a novel cloud-model-enhanced TOPSIS (technique for order of preference by similarity to ideal solution) method is proposed to rank alternative production scheduling schemes. A practical example is presented to show the implementation details and demonstrate the feasibility of our proposed method. The results and comparative analysis indicate that our hybrid MCGDM method is more reasonable, flexible, practical, and effective in evaluating and ranking production scheduling schemes in an uncertain environment.

Threshold-Based Value-Driven Method to Support Consensus Reaching in Multicriteria Group Sorting Problems: A Minimum Adjustment Perspective

In multicriteria group decision-making (MCGDM) problems, there exist the situations that alternatives need to be assigned to several predefined ordered categories rather than be ranked from the most preferred to the least preferred, which is called multicriteria group sorting problems. To address multicriteria group sorting problems, it is necessary to implement a consensus reaching process to fully consider the opinion of each decision maker and reduce the conflict among them. To do so, this article proposes a consensus reaching model for multicriteria group sorting problems based on the threshold-based value-driven sorting method from the perspective of minimum adjustment. Specifically, we first define the consensus measure to calculate the agreement degree among decision makers by considering the ordinal information and cardinal information at the same time. On this basis, we construct a minimum adjustment optimization model in terms of the threshold-based value-driven sorting method to assist decision makers in modifying their decision matrices and further promote consensus. Followed by this, an optimization model that aims to minimize the distance between all decision makers and the group with respect to alternatives’ comprehensive values and sorting results is developed to determine the group sorting result for alternatives. Moreover, a numerical application of urban park management, some sensitivity analysis, and simulation experiments are provided to justify the proposed method. Experimental results reveal that the proposed method is effective in promoting consensus.

Multi-Criteria Group Decision-Making with ELECTRE-III Method for Selection of Female Spouse in Pythagorean Neutrosophic Environment

Selecting a female partner in the 21st century is more challenging as compared to the 20th century. The globalized world, changing societal norms, and technology have increased the pool of potential partners, making it harder to find a compatible match. The prevalence of social media and online dating has also changed how people interact, leading to new challenges in establishing genuine connections. This paper presents a novel Multiple-Criteria Group Decision Making (MCGDM) model for selecting a female spouse using the ELECTRE-III method in a Pythagorean neutrosophic environment. The proposed model takes into account multiple criteria and addresses the challenges of handling conflicting and uncertain information. The Pythagorean neutrosophic set theory (PNST) is used to handle the vagueness and uncertainty of the decision-making process. The proposed model is validated using a case study of selecting a female spouse based on education, family background, beauty, and skill capability. The case study results demonstrate the proposed model's effectiveness in addressing the complexity and uncertainty of the decision-making process and providing a useful tool for decision-makers in selecting a spouse.

Development of [formula omitted] quasirung orthopair fuzzy hamacher aggregation operators and its application in decision-making problems

The concept of p,q− quasirung orthopair fuzzy (p,q− QOF) sets is an advanced extension of q− rung orthopair fuzzy sets (q− ROFSs). This paper introduces the adaptation of Hamacher t-norm and t-conorm to the p,q− QOF environment. A series of Hamacher aggregation operators (AOs) and their associated properties are presented. This study extends its application to multi-criteria group decision-making (MCGDM) for practical problem-solving, illustrated through the analysis of mobile payment platforms. The influence of the aggregation operator parameters, denoted as p and q, on the outcomes of decisions is effectively showcased. Moreover, a comparative analysis is carried out to validate the credibility and authenticity of the proposed model. Finally, the advantages and limitations of the proposed model are outlined.

An improved failure mode and effect analysis method for group decision-making in utility tunnels construction project risk evaluation

The risk factors of utility tunnels construction project (UTCPs) are diverse and complex, which can easily lead to serious accidents. And these accidents are usually the result of ignoring the most serious risk sources due to the lack of comprehensive risk evaluations. Therefore, this paper proposes an improved failure mode and effect analysis (FMEA) multi-criteria group decision model for utility tunnels construction project risk evaluation. First, expert groups are invited to evaluate the project risk failure modes, and k-means clustering is used to group the experts and form the aggregated matrix. Then, the CCSD (correlation coefficient and standard deviation) method, regret theory and MULTIMOORA method are used to rank the failure modes. Subsequently, the superiority of the model is illustrated by sensitive and comparative analyzes through a case study of the utility tunnels construction project for Beijing Winter Olympics. Finally, a systematic application model is proposed to provide some decision basis for project risk management.

Modified MABAC for MCGDM with interval-valued neutrosophic sets and application to design quality evaluation of digital cultural and creative products

With the development of digital creative industry and the use of more emerging digital technologies, the forms of digital cultural and creative design products are also increasingly diversified. Unlike traditional cultural and creative design products, digital cultural and creative design products are no longer limited to physical products, but appear more in the field of exhibition, virtual reality and product visualization. At the initial stage of the combination of digital information technology and cultural and creative content, digital cultural and creative design products, unlike ordinary cultural and creative design products, opened a new vision for users. The design quality evaluation of digital cultural and creative design products is viewed as a multi-criteria group decision-making (MCGDM). The single-value neutrosophic sets (SVNSs) concept and its interval-valued version (Interval-valued neutrosophic sets, IVNSs) are within the recent rapid developments for managing the uncertain representation problem in MCGDM. In SVNSs, decision makers (DMs) could portray membership, non-membership and hesitancy. IVNSs expands this useful feature through portraying intervals to these three information decision degrees. In this manner, the uncertainty, ambiguity and vagueness hidden in human judgements could be quantified more efficiently. IVNSs have been widely employed and researched in MCGDM. The main purpose of this paper is to proposed the Interval-valued neutrosophic number MABAC (IVNN-MABAC) technique based on prospect theory (PT) to address the MCGDM. Eventually, an example for design quality evaluation of digital cultural and creative design products and some comparative analysis was employed to demonstrate the superiority of the designed technique.