Search Results (45)

To effectively deal with the uncertainty of value assessments of industry-characteristic universities, this paper proposes a new fuzzy multi-attribute assessment method. Firstly, we define the complex cubic fractional orthotriple fuzzy set (CCFOFS) for expressing ambiguous information and present some basic operational rules and information measures. Then, we present the complex cubic fractional orthotriple fuzzy Dombi-weighted power-partitioned Muirhead mean (CCFOFDWPPMM) operator, which combines the superiority of the Dombi operations, power average (PA) operator, and partitioned Muirhead mean (PMM) operator. Further, a multi-attribute assessment method is constructed based on the CCFOFDWPPMM operator and the Integrated Determination of Objective Criteria Weights (IDOCRIW) method. Furthermore, we constructed a novel assessment index system for the construction of first-class disciplines. Finally, this paper verifies the validity and applicability of the method by applying the novel multi-attribute assessment method to a practical case of first-class discipline construction in industry-characteristic universities. Full article

The rapid growth of e-commerce has created substantial environmental impacts, driving the need for advanced optimization models to enhance supply chain sustainability. As consumer preferences shift toward environmental responsibility, organizations must adopt robust quantitative methods to reduce ecological footprints while ensuring operational efficiency. This study develops a novel hybrid multi-criteria decision-making (MCDM) model to evaluate and prioritize green suppliers under uncertainty, integrating the rough-Dombi best–worst method (BWM) and an improved Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The proposed model addresses two key challenges: (1) inconsistency in expert judgments through rough set theory and Dombi aggregation operators and (2) ranking instability via an enhanced TOPSIS formulation that mitigates rank reversal. Mathematically, the rough-Dombi BWM leverages interval-valued rough numbers to model subjective expert preferences, while the Dombi operator ensures flexible and precise weight aggregation. The modified TOPSIS incorporates a dynamic distance metric to strengthen ranking robustness. A case study of five e-commerce suppliers validates the model’s effectiveness, with results identifying cost, green competitiveness, and external environmental management as the dominant evaluation dimensions. Key indicators—such as product price, pollution control, and green design—are rigorously prioritized using the proposed framework. Theoretical contributions include (1) a new rough-Dombi fusion for criteria weighting under uncertainty and (2) a stabilized TOPSIS variant with reduced sensitivity to data perturbations. Practically, the model provides e-commerce enterprises with a computationally efficient tool for sustainable supplier selection, enhancing resource allocation and green innovation. This study advances the intersection of uncertainty modeling, operational research, and sustainability analytics, offering scalable methodologies for mathematical decision-making in supply chain contexts. Full article

Trapezoidal-valued intuitionistic fuzzy numbers (TrVIFNs) are the real generalizations of intuitionistic fuzzy numbers, interval-valued intuitionistic fuzzy numbers, and triangular intuitionistic fuzzy numbers, which effectively model real-life problems that consist of imprecise and incomplete data. This study incorporates the Aczel-Alsina aggregation operators (which consist of parameter-based flexibility) for solving any group of decision-making problems modeled in a trapezoidal-valued intuitionistic fuzzy (TrVIF) environment. In this study, we first define new operations on TrVIFNs based on the Aczel-Alsina operations. Secondly, we introduce new trapezoidal-valued intuitionistic fuzzy aggregation operators, such as the TrVIF Aczel-Alsina weighted averaging operator, the TrVIF Aczel-Alsina ordered weighted averaging operator, and the TrVIF Aczel-Alsina hybrid averaging operator, and we discuss their fundamental mathematical properties by examining various theorems. This study also includes a new algorithm named ‘three-stage multi-criteria group decision-making’, where we obtain the criteria weights using the newly proposed TrVIF-MEREC method. Additionally, we introduce a new modified algorithm called TrVIF-WASPAS to solve the multi-criteria decision-making (MCDM) problem in the trapezoidal-valued intuitionistic fuzzy environment. Then, we apply this proposed method to solve a model case study problem involving location selection for a wind power plant project. Then, we discuss the proposed algorithm’s sensitivity analysis by changing the criteria weights concerning different parameter values. Finally, we compare our proposed methods with various existing methods, like some subclasses of TrVIFNs such as IVIFWA, IVIFWG, IVIFEWA, and IVIFEWG, and also with some MCGDM methods of TrVIFNs, such as the Dombi aggregation operator-based method in TrVIFNs and the TrVIF-Topsis method-based MCGDM, to show the efficacy of our proposed algorithm. This study has many advantages, as it consists of a total ordering principle in ranking alternatives in the newly proposed TrVIF-MCGDM techniques and TrVIF-WASPAS MCDM techniques for the first time in the literature. Full article

In engineering and decision sciences, trapezoidal-valued neutrosophic fuzzy numbers $(TzVNFNs)$ have become effective tools for managing imprecision and uncertainty in multi-attribute group decision-making (MAGDM) problems. This work introduces accumulation operators based on the Dombi t-norm $(D{T}_n)$ and Dombi t-conorm $(D{T}_{cn})$ specifically designed for $TzVNFNs$. These operators enhance the flexibility, consistency, and fairness of the aggregation process. To demonstrate their practical applicability, we propose three novel geometric aggregation operator’s namely, the trapezoidal-valued neutrosophic fuzzy Dombi weighted geometric ($TzVNFDWG$), the trapezoidal-valued neutrosophic fuzzy Dombi ordered weighted geometric ($TzVNFDOWG$), and the trapezoidal-valued neutrosophic fuzzy Dombi hybrid Geometric ($TzVNFDHG$) operators. These are incorporated into a systematic MAGDM framework to support the selection of optimal locations for charging stations. Comparative analysis with current decision-making methodologies highlights the efficacy and benefits of the suggested method. The suggested method provides a flexible and mathematically based choice framework designed for uncertain condition. Full article

Trapezoidal-valued fermatean fuzzy numbers (TpVFFNs) are essential for handling daily decision-making issues in the engineering and management fields. Accumulation processes on the set of TpVFFN are used to address decision-making problems described in this environment as necessary. The primary goal of this paper is to provide the concept of Dombi t-norm $\left(D_{tn}\right)$- and Dombi t-conorm $\left(D_{tcn}\right)$-based accumulation operators on the class of TpVFFN, emphasizing how they behave symmetrically in aggregation processes to maintain consistency and fairness. To use s to illustrate mathematical circumstances, we first create a trapezoidal-valued fermatean fuzzy Dombi’s weighted geometric operator, hexagonal hybird geometric operator, fermatean fuzzy order weighted geometric operator. Second, we use a multi-attribute group decision-making (MAGDM) approach to compute the recommended accumulation operators. Finally, we demonstrate the potential practical application of the proposed decision-making problem related to the pink cab. Full article

It was recently proposed to extend the spherical fuzzy set to spherical fuzzy credibility sets (SFCSs). In this paper, we define the concept of SFCSs. We then define new operational laws for SFCSs using Dombi operational laws. Various spherical fuzzy credibility aggregation operators such as spherical fuzzy credibility Dombi weighted averaging (SFCDWA), spherical fuzzy credibility Dombi ordered weighted averaging (SFCDOWA), spherical fuzzy credibility Dombi weighted geometric (SFCDWG), and spherical fuzzy credibility Dombi ordered weighted geometric (SFCDOWG) are defined. We also show the boundedness, monotonicity, and idempotency aspects of the suggested operators. We proposed the spherical fuzzy credibility entropy to find the unknown weight information of the attributes. Symmetry analysis is a useful and important tool in artificial intelligence that may be used in a variety of fields. To calculate the significant factor, we determine the multi-attribute decision-making (MADM) method using the suggested operators for SFCSs to increase the value of the assessed operators. To demonstrate the effectiveness and superiority of the suggested approach, we compare our findings to those of many other approaches. Full article

In this research, we introduce the intuitionistic hesitant fuzzy rough set by integrating the notions of an intuitionistic hesitant fuzzy set and rough set and present some intuitionistic hesitant fuzzy rough set theoretical operations. We compile a list of aggregation operators based on the intuitionistic hesitant fuzzy rough set, including the intuitionistic hesitant fuzzy rough Dombi weighted arithmetic averaging aggregation operator, the intuitionistic hesitant fuzzy rough Dombi ordered weighted arithmetic averaging aggregation operator, and the intuitionistic hesitant fuzzy rough Dombi hybrid weighted arithmetic averaging aggregation operator, and demonstrate several essential characteristics of the aforementioned aggregation operators. Furthermore, we provide a multi attribute decision-making approach and the technique of the suggested approach in the context of the intuitionistic hesitant fuzzy rough set. A real-world problem for selecting a suitable worldwide partner for companies is employed to demonstrate the effectiveness of the suggested approach. The sensitivity analysis of the decision-making results of the suggested aggregation operators are evaluated. The demonstrative analysis reveals that the outlined strategy has applicability and flexibility in aggregating intuitionistic hesitant fuzzy rough information and is feasible and insightful for dealing with multi attribute decision making issues based on the intuitionistic hesitant fuzzy rough set. In addition, we present a comparison study with the TOPSIS approach to illustrate the advantages and authenticity of the novel procedure. Furthermore, the characteristics and analytic comparison of the current technique to those outlined in the literature are addressed. Full article

Against the background of a major change in the world unseen in a century, emergencies with high complexity and uncertainty have had serious impacts on economic security and sustainable social development, making emergency management an important issue that needs to be urgently resolved, and the quality assessment of emergency information is a key link in emergency management. To effectively deal with the uncertainty of emergency information quality assessment, a new fuzzy multi-attribute assessment method is proposed in this paper. First, we propose the linguistic complex T-spherical fuzzy set (LCT-SFS), which can deal with two-dimensional problems and cope with situations in which assessment experts cannot give quantitative assessments. Then, the advanced linguistic complex T-spherical fuzzy Dombi-weighted power-partitioned Heronian mean (ALCT-SFDWPPHM) operator, which incorporates the flexibility of Dombi operations, is proposed. The partitioned Heronian mean (PHM) operator can consider attribute partitioning and attribute correlation, the power average (PA) operator can eliminate the effect of evaluation singularities, and the advanced operator can circumvent the problem of consistent or indistinguishable aggregation results, which provides a strong comprehensive advantage in the evaluating information aggregation. Finally, a fuzzy multi-attribute assessment model is constructed by combining the proposed operator with the WASPAS method and applied to the problem of assessing the quality and sensitivity of emergency information; qualitative and quantitative comparison analyses are carried out. The results show the method proposed in this paper has strong feasibility and validity and can represent uncertainty assessment more flexibly while providing reasonable and reliable results. The method can provide new ideas and methods for the quality assessment of emergency information, and promoting sustainable, efficient, and high-quality development of emergency management. Full article

Circular q-rung orthopair fuzzy sets (FSs) were recently considered as an extension of q-rung orthopair FSs (q-ROFSs), circular intuitionistic FSs (Cir-IFSs), and circular Pythagorean FSs (Cir-PFSs). However, they are only considered for some simple algebraic properties. In this paper, we advance the work on circular q-ROFSs (Cirq-ROFSs) in Dombi aggregation operators (AOs) with more mathematical properties of algebraic laws. These include the circular q-rung orthopair fuzzy (Cirq-ROF) Dombi weighted averaging (Cirq-ROFDWA), Cirq-ROF Dombi ordered weighted averaging (Cirq-ROFDOWA), Cirq-ROF Dombi weighted geometric (Cirq-ROFDWG), and Cirq-ROF Dombi ordered weighted geometric (Cirq-ROFDOWG) operators. Additionally, we present the properties of idempotency, monotonicity, and boundedness for the proposed operators. In the context of artificial intelligence, symmetry analysis plays a significant and efficient role that can refer to several aspects. Thus, to compute the major aspect, we identify the multi-attribute decision-making (MADM) technique based on the proposed operators for Cirq-ROF numbers (Cirq-ROFNs) to enhance the worth of the evaluated operators. Finally, we use some existing techniques for comparison to our results to show the validity and supremacy of the proposed method. Full article

Three-dimensional printers (3DPs), as critical parts of additive manufacturing (AM), are state-of-the-art technologies that can help practitioners with digital transformation in production processes. Three-dimensional printer performance mostly depends on good integration with artificial intelligence (AI) to outperform humans in overcoming complex tasks using 3DPs equipped with AI technology, particularly in producing an object with no smooth surface and a standard geometric shape. Hence, 3DPs also provide an opportunity to improve engineering applications in manufacturing processes. As a result, AM can create more sustainable production systems, protect the environment, and reduce external costs arising from industries’ production activities. Nonetheless, practitioners do not have sufficient willingness since this kind of transformation in production processes is a crucial and irrevocable decision requiring vast knowledge and experience. Thus, presenting a methodological frame and a roadmap may help decision-makers take more responsibility for accelerating the digital transformation of production processes. The current study aims to fill the literature’s critical theoretical and managerial gaps. Therefore, it suggests a powerful and efficient decision model for solving 3DP selection problems for industries. The suggested hybrid FF model combines the Fermatean Fuzzy Stepwise Weight Assessment Ratio Analysis (FF–SWARA) and the Fermatean Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval (FF–RAFSI) approaches. The novel FF framework is employed to solve a critical problem encountered in the automobile manufacturing industry with the help of two related case studies. In addition, the criteria are identified and categorized regarding their influence degrees using a group decision approach based on an extended form of the Delphi with the aid of the Fermatean fuzzy sets. According to the conclusions of the analysis, the criteria “Accuracy” and “Quality” are the most effective measures. Also, the suggested hybrid model and its outcomes were tested by executing robustness and validation checks. The results of the analyses prove that the suggested integrated framework is a robust and practical decision-making tool. Full article

Using green energy is an important way for businesses to achieve their ESG goals and ensure sustainable operations. Currently, however, green energy is not a stable source of power, and this instability poses certain risks to normal business operations and manufacturing processes. The installation of energy storage equipment has become an indispensable accompaniment to facilitating green energy use for an enterprise. However, businesses may encounter significant barriers during the process of installing energy storage equipment. This study aims to explore and discern the key barrier factors that influence the assessment and decision-making process of installing energy storage equipment. A hybrid approach combining the Decision-making and Trial Evaluation Laboratory (DEMATEL) and Interpretive Structural Modeling (ISM) is developed to explore the causality relationships and degrees of influence among these key factors. The Z-number and Rough Dombi Weighted Geometric Averaging (RDWGA) methods are also utilized to integrate the experts’ varied opinions and uncertain judgements. Finally, recommendations are provided based on the results to assist businesses to make informed decisions while evaluating the installation of energy storage equipment, to ensure a stable and uninterrupted supply of green energy for use in normal operations. Full article

The sustainable development of mountain tourism is crucial for preserving the delicate ecosystems and resources found in these unique landscapes. This research paper investigates the sustainability of mountain lodges, which serve as essential facilities for delivering mountain tourism services. To assess sustainability, expert decision making involving eight selected experts was employed. A hybrid approach combining the IMF SWARA (IMproved Fuzzy Step-wise Weight Assessment Ratio Analysis) method with Fuzzy Dombi Aggregation Operators was utilized to determine the weights of various sustainability criteria. The IMF SWARA method assigned initial weights based on expert input, which were subsequently adjusted using Fuzzy Dombi Aggregation Operators. The findings highlight the significance of two key criteria as per expert evaluations: the quality of the services offered (C21) and the preservation of natural resources (C15). To rank and evaluate the mountain lodges, the fuzzy CRADIS (Compromise Ranking of Alternatives from Distance to Ideal Solution) method was employed, ultimately identifying Zabrana (ML6) as the top-ranked mountain lodge. The validity of these results was confirmed through result validation and sensitivity analysis. This research contributes by providing insights into the current state of mountain tourism and offering guidelines for enhancing the overall mountain tourism experience through the integration of fuzzy methods. Full article

Due to the complexity and uncertainty of decision-making, probabilistic linguistic term sets (PLTSs) are currently important tools for qualitative evaluation of decision-makers. The asymmetry of evaluation information can easily lead to the loss of subjective preference information for decision-makers, and the existing operation of decision-maker evaluation information fusion operators is difficult to solve this problem. To solve such problems, this paper proposes some new operational methods for PLTSs based on Dombi T-conorm and T-norm. Considering the interrelationships between the input independent variables of PLTSs, the probabilistic linguistic weighted Dombi Bonferroni mean Power average (PLWDBMPA) operators are extended and the properties of these aggregation operators are proposed. Secondly, the PLWDBMPA operator is used to fuse the evaluation information of decision-makers, avoiding the loss of decision information as much as possible. This paper uses social media platforms and web crawler technology to obtain online comments from users on decision-making to obtain the public’s attitude towards decision events. TF-IDF and Word2Vec are used to calculate the weight of alternatives on each attribute. Under traditional group decision-making methods and integrating the wisdom of the public, a novel multi-attribute group decision-making method based on TODIM method is proposed. Finally, the case study of Turkey earthquake shelter selection proves this method is scientific and effective. Meanwhile, the superiority of this method was further verified through comparisons with the PL-TOPSIS, PLWA, SPOTIS and PROMETHEE method. Full article

Information disclosure is an important prerequisite and guarantee for the government to answer public health incidents in a timely manner, and is also a basic requirement for the management of emergencies. Evaluating the information disclosure on public health incidents is conducive to improving the quality of emergency information disclosure and comprehensively enhancing the emergency answer and treatment ability of public health incidents. In response to the complex uncertainties in the assessment of information disclosure on public health incidents, this paper proposes a new fuzzy multi-attribute evaluation method. First, a multi-attribute evaluation system for the assessment of information disclosure on public health emergencies is proposed. Then, a novel approach to information disclosure assessment is proposed on the basis of Dombi power divided Muirhead mean operators of fractional orthotriple fuzzy, which can fully consider the relationship between properties and the division of relationships within properties and reduce the distortion in the evaluation process. Meanwhile, it can avoid the impact of singular values on the overall evaluation outcomes of the government. In the end, the effectiveness and flexibility of the approach are validated through an empirical study of a real-life case with comparative analysis and sensitivity analysis. Full article

The sustainability of the climate is a critical concern in the modern world. A variety of acts are included in sustainability that strive to lessen our carbon footprint and maintain the fragile balance of our world. To preserve a sustainable future for future generations, we must cooperate in adopting renewable energy sources, supporting green transportation, and implementing responsible land use. In this article, we propose the concepts of complex intuitionistic fuzzy Dombi hybrid averaging (CIFDHA) and complex intuitionistic fuzzy Dombi hybrid geometric (CIFDHG) operators within the framework of a complex intuitionistic fuzzy environment. Furthermore, we explore several additional important features of these operators. To overcome the limitations of the existing score function within the CIF knowledge context, we present a new and improved score function. Additionally, we apply the proposed score function and newly defined operators to select an optimal strategy for mitigating the drivers of climate change and saving the planet’s valuable resources for a more livable and resilient planet. In order to demonstrate the validity and practicality of the suggested strategies, we conducted a comparative study of these novel techniques with existing methods. Full article