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Single-valued neutrosophic sets (SVNSs) and their application to material selection in engineering design. Liquid hydrogen is a feasible ingredient for energy storage in a lightweight application due to its high gravimetric power density. Material selection is an essential component in engineering since it meets all of the functional criteria of th...
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... warming, renewable primary energies will enter the picture, either for financial or ecological reasons. In terms of energy content, weight, and volume, the newly produced hydrogen fuel differs significantly from the commonly used ones. The lightweight of hydrogen in comparison to its energy capacity is the most notable feature, as depicted in Fig. 2. The energy content of hydrogen gas per kg is 120 MJ, which is three times that of gasoline and diesel fuel. The advantage over methanol is sixfold ...
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... Furthermore, in the literature, aggregation operators based on various operations, such as Yager operations, are also utilized. Among these operations are Archimedean aggregation operators (Seikh & Mandal, 2023b), Aczel-Alsina aggregation operators (Naseem et al., 2023), Hamacher aggregation operators (Liu et al., 2014), Schweizer-Sklar aggregation operators (Kara et al., 2024b), Dombi aggregation operators (Chen & Ye, 2021), Dombi power aggregation operators (Jana & Pal, 2021), Dombi Bonferroni aggregation operators (Peng & Smarandache, 2019), and Einstein interactive aggregation operators (Farid & Riaz, 2022). ...
Fish cages are crucial for the establishment of sustainable fish farms. The selection of fish cages is an essential subject to be examined for ensuring sustainability. This research introduces an advanced decision support model for the selection of fish cage types used in fish farming in reservoirs (R-FFs). The decision support model is based on multi-criteria decision-making (MCDM) approach and utilizes type-2 neutrosophic numbers (T2NNs). The importance levels of criteria are determined using the T2NN-Entropy method, and the ranking of fish cage types is achieved through the alternative ranking order method accounting for two-step normalization (AROMAN). The developed model is referred to as the T2NN-Entropy-AROMAN hybrid method and relies on expert opinions. Two advanced aggregation operators based on Yager t-norm and t-conorm operations, named T2NN Yager weighted arithmetic mean and T2NN Yager weighted geometric mean, are developed for aggregating T2NNs. The validity of these two aggregation operators is demonstrated. A real-life case study is developed to confirm the applicability of the T2NN-Entropy-AROMAN hybrid method. This case study focuses on the selection of fish cage types for the Artvin-Borçka R-FF in Artvin province, Turkey. The research results indicate that floating cages are the best alternative type for sustainable fish farming. Sensitivity analysis scenarios confirm the robustness of the research model and findings. The research findings, coupled with the developed model, offer valuable insights and guidance to decision-makers, researchers, and practitioners within the sector.
... In general, neutrosophic sets (NSs) [6] are not only the extended form of fuzzy sets (FSs) [7] and intuitionistic FSs [8], but also independently depict inconsistent, uncertain, and incomplete information though the true, false, and uncertain membership values, which FSs and intuitionistic FSs cannot do. Although existing fuzzy, intuitionistic fuzzy, and neutrosophic decision making methods and applications [9][10][11][12][13][14][15][16][17][18][19][20] have contained a lot of studies in existing literature, but they do not consider the credibility measures of various evaluation values in uncertain and ambiguous setting. To guarantee the credibility degrees of fuzzy values in uncertain and ambiguous environments, Ye et al. [21] first proposed fuzzy credibility values and their aggregation operators to perform the multiple attribute decision making (MADM) application in the selection of slope design schemes. ...
This paper aims to develop a MAGDM model using single-valued neutrosophic credibility matrix (SVNCM) energy in a SVNCM scenario. To do it, first, SVNCM energy and its score function are presented as a conceptual extension of existing single-valued neutrosophic matrix (SVNM) energy. Then, a MAGDM model is developed in terms of SVNCM energy and its score function in a SVNCM scenario and also its decision algorithm is provided to solve MAGDM problems with SVNCMs. Finally, the developed MAGDM model is applied in the school site selection problem as an actual example, then the comparative investigation of the decision results in the SVNM and SVNCM scenarios indicates the superiority of the developed model over existing MAGDM model.
... AOscompound all the input data into a single entity and so they have been efficaciously employed for information processing, specifically decision-making, shape recognition, data analytics, and neural networks. The existing SVN AOs are mainly limited to: SVN weighted algebraic and geometric operators [66], SVN Dombi weighted algebraic and geometric operators [67], SVN Hamacher weighted algebraic and geometric operators [68], and SVN Einstein weighted algebraic and geometric operators [69]. The existing SVN AOs [66][67][68][69] fail to provide proper generalization and resilience in changing risk choices while aggregating preferences for making decisions. ...
... The existing SVN AOs are mainly limited to: SVN weighted algebraic and geometric operators [66], SVN Dombi weighted algebraic and geometric operators [67], SVN Hamacher weighted algebraic and geometric operators [68], and SVN Einstein weighted algebraic and geometric operators [69]. The existing SVN AOs [66][67][68][69] fail to provide proper generalization and resilience in changing risk choices while aggregating preferences for making decisions. ...
... (i) The present AOs [66][67][68][69] lack resilience and prevalence.It renders them less useful when combining decision-making preferences in the SVN scenario and changing risk preferences. On the other hand, Archimedean AOs are well known for its generality as many of the existing operators like algebraic AOs, Einstein AOs, Hamachar AOs and Frank AOs can be derived as special cases of Archimedean AOs. ...
Selecting the right educational vendors in the Metaverse, particularly those utilizing extended reality (XR), is crucial for creating an engaging and immersive learning environment. Careful vendor selection ensures the delivery of high-quality XR educational content, considering factors such as seamless integration with different XR devices and addressing associated challenges, which can affect the comfort and well-being of learners. This paper proposes a decision-making model to address the complex task of selecting educational vendors within the Metaverse with a focus on extended reality (XR). Recognizing the challenges inherent in such selections, this work presents a consensus-based measurement of alternatives and ranking according to compromise solution (MARCOS) model, incorporating single-valued neutrosophic (SVN) information and SVN Dombi-Archimedean weighted aggregation operators. Attribute weights crucial for decision-making are determined through an optimization tool employing cross-entropy measures with partial weight information. The evaluation encompasses nine criteria, including cost, security, privacy, pedagogical alignment, configuration, maintenance, level of control, output tools, degree of immersion, availability of XR learning contents, and time. Four leading vendors including Victory XR, ARuVR, zSpace, and Varjo Technologies are assessed, with zSpace emerging as the most favorable alternative with the highest overall utility value of 0.6889. The paper further conducts sensitivity analysis and performance comparisons to establish the robustness of the ranking results, providing a comprehensive methodology for educational stakeholders addressing the evolving dynamics of the Metaverse.
... Previous AOs [40][41][42][43][44] have been proposed to handle MADM problems under fuzzy environments, but few have addressed the unbiased treatment of MD and NMD. Consolidated values reported in the literature [45][46][47][48] cannot be differentiated when a decision-maker compares both MD and NMD, indicating favoritism in the verdict. ...
The main goal of informal computing is to overcome the limitations of hypersensitivity to defects and uncertainty while maintaining a balance between high accuracy, accessibility, and cost-effectiveness. This paper investigates the potential applications of intuitionistic fuzzy sets (IFS) with rough sets in the context of sparse data. When it comes to capture uncertain information emanating from both upper and lower approximations, these intuitionistic fuzzy rough numbers (IFRNs) are superior to intuitionistic fuzzy sets and pythagorean fuzzy sets, respectively. We use rough sets in conjunction with IFSs to develop several fairly aggregation operators and analyze their underlying properties. We present numerous impartial laws that incorporate the idea of proportionate dispersion in order to ensure that the membership and non-membership activities of IFRNs are treated equally within these principles. These operations lead to the development of the intuitionistic fuzzy rough weighted fairly aggregation operator (IFRWFA) and intuitionistic fuzzy rough ordered weighted fairly aggregation operator (IFRFOWA). These operators successfully adjust to membership and non-membership categories with fairness and subtlety. We highlight the unique qualities of these suggested aggregation operators and investigate their use in the multi-attribute decision-making field. We use the intuitionistic fuzzy rough environment's architecture to create a novel strategy in situation involving several decision-makers and non-weighted data. Additionally, we developed a novel technique by combining the IFSs with quaternion numbers. We establish a unique connection between alternatives and qualities by using intuitionistic fuzzy quaternion numbers (IFQNs). With the help of this framework, we can simulate uncertainty in real-world situations and address a number of decision-making problems. Using the examples we have released, we offer a sophisticated and systematically constructed illustrative scenario that is intricately woven with the complexity of medical evaluation in order to thoroughly assess the relevance and efficacy of the suggested methodology.
... Based on multiple variables, many types of TNM and TCNM have been introduced. A few examples of TNMs and TCNMs include Dombi [32], Frank [33], Einstein [34], and Hamacher [35]. Due to the desirable characteristics of TNMs and TCNMs, they have been also used in information fusion in the case of fuzzy environments. ...
The fusion of information is a very hectic process whenever we analyze the information. Several frameworks have been introduced to reduce the uncertainty while fusing the information. Among those techniques, the Pythagorean fuzzy rough set (PyFRS), which is based on approximations is a key idea for dealing with uncertainty when data is taken from real-world circumstances. Furthermore, the most adaptable and flexible operational laws based on the parameters for fuzzy frameworks are Aczel-Alsina t-norm (AATNM) and Aczel-Alsina t-conorm (AATCNM). The major goal of this work is to introduce some methods for the basic operations of the information in the shape of Pythagorean fuzzy rough (PyFR) values (PyFRVs). Consequently, the PyFR Aczel-Alsina weighted geometric (PyFRAAWG), PyFR Aczel-Alsina ordered weighted geometric (PyFRAAOWG), and PyFR Aczel-Alsina hybrid weighted geometric (PyFRAAHWG) operators are developed in this article based on AATNM and AATCNM. Further, some basic properties of the developed operators are observed and discussed. Further, the developed approaches are applied to the problem of multi-attribute group decision-making (MAGDM). The obtained results from the MAGDM problem are observed at various values of the parameters involved by AATNM and AATCNM. Moreover, the results are also compared with already existing techniques for the significance of the developed approach.
... The results of the analysis shown the following: the hybrid method which was the combination of two or more MCDM methods was the most applied technique for material selection in all application areas identified; the most frequently applied decision criteria for selecting ideal alternative was the cost; the highest number of articles on material selection was published in 2013; the most significant journal was materials and design and finally, the country with the highest application of MCDM method was India. Farid & Riaz (2022) proposed MCDM approach for material selection of cryogenic storage containers was developed. Additionally, the authenticity analysis and comparison analysis were designed to discuss the validity and rationality of the optimal decision. ...
Material selection plays a pivotal role in engineering and design, profoundly influencing product performance, cost, and sustainability. Traditional approaches to material selection typically involve an intricate interplay of multiple criteria, encompassing mechanical properties, environmental impact, cost, and availability. To grapple with this complexity, multi-criteria decision-making (MCDM) methods have risen to prominence as systematic frameworks for facilitating well-informed material selection decisions. MCDM methods offer a structured approach to evaluating and ranking materials based on a set of criteria, thereby empowering engineers and designers to make informed choices. In this paper, Measurement of Alternatives and Ranking According to Compromise Solution (MARCOS) method has been employed to determine the most suitable material for sintered pulleys used in automobiles. CRiteria Importance Through Intercriteria Correlation (CRITIC) method is applied to assign criteria weights. The analysis reveals that sintered hardened steel emerges as the best choice for sintered pulleys in automotive applications. To validate the outcomes obtained from the proposed method, a performance analysis has been conducted, comparing the results with those generated by other well-established MCDM methods. Additionally, a sensitivity analysis has been carried out using Spearman rank correlation coefficient.
... q-ROFSs have been used for personal mobility in the metaverse with driverless cars, socially responsible rehabilitation of mining sites, and floating offshore wind farm site selection in Norway Deveci, Gokasar & Brito-Parada, 2022;. Farid & Riaz (2022), proposed some AOs with applications to green supplier selection and Liu & Wang (2018) introduced interval-valued intuitionistic fuzzy Schweizer-Sklar power AOs with supplier selection applications. Liu et al. (2022) used the techniques of the operational science for green supplier selection with cross-entropy and Archimedean AOs. ...
In recent years, as corporate consciousness of environmental preservation and sustainable growth has increased, the importance of sustainability marketing in the logistic process has grown. Both academics and business have increased their focus on sustainable logistics procedures. As the body of literature expands, expanding the field's knowledge requires establishing new avenues by analyzing past research critically and identifying future prospects. The concept of "q-rung orthopair fuzzy soft set" (q-ROFSS) is a new hybrid model of a q-rung orthopair fuzzy set (q-ROFS) and soft set (SS). A q-ROFSS is a novel approach to address uncertain information in terms of generalized membership grades in a broader space. The basic alluring characteristic of q-ROFS is that they provide a broader space for membership and non-membership grades whereas SS is a robust approach to address uncertain information. These models play a vital role in various fields such as decision analysis, information analysis, computational intelligence, and artificial intelligence. The main objective of this article is to construct new aggregation operators (AOs) named "q-rung orthopair fuzzy soft prioritized weighted averaging" (q-ROFSPWA) operator and "q-rung orthopair fuzzy soft prioritized weighted geometric" (q-ROFSPWG) operator for the fusion of a group of q-rung orthopair fuzzy soft numbers and to tackle complexities and difficulties in existing operators. These AOs provide more effective information fusion tools for uncertain multi-attribute decision-making problems. Additionally, it was shown that the proposed AOs have a higher power of discriminating and are less sensitive to noise when it comes to evaluating the performances of sustainable logistic providers.
... To conduct the comparison, VIMM uses a scale to convert decision-makers' subjective opinions www.nature.com/scientificreports/ into numbers within an interval of [2,5,9] , in which decision-maker is able to select any rational number between these three numbers. The scale is illustrated in Fig. 3. ...
A large number of materials and various criteria fashion material selection problems as complex multicriteria decision-making (MCDM) problems. This paper proposes a new decision-making method called the simple ranking process (SRP) to solve complex material selection problems. The accuracy of the criteria weights has a direct impact on the outcomes of the new method. In contrast to current MCDM
methods, the normalization step has been eliminated from the SRP method as a potential source of producing incorrect results. The application of the method is appropriate for situations with high levels of complexity in material selection because it only considers the ranks of alternatives in each criterion. The first scenario of vital-immaterial mediocre method (VIMM) is used as a tool to derive
criteria weights based on expert assessment. The result of SRP is compared with a number of MCDM methods. In order to evaluate the findings of analytical comparison, a novel statistical measure known as compromise decision index (CDI) is proposed in this paper. CDI revealed that the MCDM methods’ outputs for solving the material selection could not be theoretically proven and requires to be evaluated through practice. As a result, the dependency analysis-an additional innovative statistical measure is introduced to demonstrate the reliability of MCDM methods by assessing its dependency on criteria weights. The findings demonstrated that SRP is extremely reliant on criteria weights and its reliability rises with the number of criteria, making it a perfect tool for solving challenging MCDM problems.
... An innovative approach to the modified TOPSIS method based on the operational aspects of sv-NS has been put forward by Biswas et al. [10]. Applications in DMP based on aggregation operators of sv-NS have been discussed by Farid et al. [11,12]. ...
The massive increase in urban population has created a slew of socioeconomic and environmental issues. Among these problems, the most notable is the disposal of solid waste and the search for an effective system for it. Many scholars employing various fuzzy set-like methodologies have considered it a fuzzy multi-criteria or multi-attribute decision-making problem due to the involvement of criteria and anticipated uncertainty. The goal of the current study is to use an innovative methodology to tackle the expected uncertainties present in the solid waste site selection problem (SOWSSP). Such uncertainties may be seen in decision-makers’ choices of parameters (or subparameters) and the degree to which they accept approximations for various options. Therefore, a novel mathematical structure called fuzzy parameterized possibility single valued neutrosophic hypersoft set (Fppsv-NHSS) is characterized first and then integrated with modified Sanchez’s method to resolve the SOWSSP through the proposal of an intelligent algorithm. The steps of the proposed algorithm are explained with a self-explanatory example. The relationship between the suitability of solid waste management systems and sites is discussed, and their rankings are determined with rich descriptions of their feasibility. The preferential aspects of this study are that it is capable of managing uncertainties depicted by the nature of parameters and approximations of alternatives by using the concept of fuzzy parameterization and possibility grades respectively. It employs particular mathematical formulations to determine the fuzzy parameterized degrees and possibility grades that are missing in the existing literature. It facilitates the decision-makers to evaluate the alternatives independently, with the choice being indeterminate. With the help of comparison, the computed results are found to be consistent and reliable due to their preferential features
... An integrated single-valued neutrosophic MCDM method based on decision-making and trial evaluation laboratory-analytical network process, geographic information system and SVN-EDAS has proposed to assess the two-stage optimal site selection for waste-to-energy plant [35]. Recently, Farid and Riaz [36] proposed new Einstein interactive aggregation operators and their application in MCDM problems under SVN environment. However, there is no study regarding the selection of LiB manufacturing plant location under indeterminate, inconsistent and uncertain environment. ...
Lithium-ion battery (LiB), a leading residual energy resource for electric vehicles (EVs), involves a market presenting exponential growth with increasing global impetus towards electric mobility. To promote the sustainability perspective of the EVs industry, this paper introduces a hybridized decision support system to select the suitable location for a LiB manufacturing plant. In this study, single-valued neutrosophic sets (SVNSs) are considered to diminish the vagueness in decision-making opinions and evade flawed plant location assessments. This study divided into four phases. First, to combine the single-valued neutrosophic information, some Archimedean-Dombi operators are developed with their outstanding characteristics. Second, an innovative utilization of the Method based on the Removal Effects of Criteria (MEREC) and Stepwise Weight Assessment Ratio Analysis (SWARA) is discussed to obtain objective, subjective and integrated weights of criteria assessment with the least subjectivity and biasedness. Third, the Double Normalization-based Multi-Aggregation (DNMA) method is developed to prioritize the location options. Fourth, an illustrative study offers decision-making strategies for choosing a suitable location for a LiB manufacturing plant in a real-world setting. Our outcomes specify that Bangalore (L2), with an overall utility degree (0.7579), is the best plant location for LiB manufacturing. The consistency and robustness of the presented methodology are discussed with the comparative study and sensitivity investigation. This is the first study in the current literature that has proposed an integrated methodology on SVNSs to select the best LiB manufacturing plant location by estimating both the objective and subjective weights of criteria and by considering ambiguous, inconsistent, and inexact manufacturing-based information.
