Spherical Fuzzy Research Articles

Analysis of cost and profit using aggregation operators on spherical fuzzy sets with confidence level

To deal with the ambiguity in real-world problems, researchers strive to obtain extensions to classical set theory. They introduced ideas like fuzzy set theory, spherical, intuitionistic, and Pythagorean fuzzy sets. In comparison to fuzzy sets, spherical fuzzy sets are more realistic at handling uncertainty. Fundamentals are classified in Spherical Fuzzy Set according to an attribute, and each feature has a variety of criteria. In this study, we have created a new extended algebraic structure called Confidence Spherical Fuzzy Aggregation Operators by applying the idea of Confidence Levels to the already-existing Spherical Fuzzy Aggregation Operators. We have created a Confidence Spherical Fuzzy Aggregation Operators-based end-product. We demonstrated various intriguing characteristics of Confidence Spherical Fuzzy Aggregation Operators, including operational laws. The study is validated by addressing the decision-making processes.

Complex spherical fuzzy Aczel Alsina aggregation operators and their application in assessment of electric cars

The multi-criteria decision-making (MCDM) tool is a robust decision-making technique utilized in several fields like networking, risk management, digital analysis, cybercrime investigation, artificial intelligence, waste management enterprises and many other selection criteria. Complex SFS (CSFS) is a new edition of the spherical fuzzy set (SFS) that offers substantial information about any item in terms of amplitude and phase terms in a wider range of real terms. Complex SFS (CSFS) can be an extension of the spherical fuzzy set (SFS). The Aczel-Alsina aggregation tools are more appropriate aggregation operators (AOs), and they are used to conquer the impact of inconsistent and uncertain data. In this paper, we reveal some new approaches based on Aczel-Alsina aggregation tools under consideration of Complex Spherical Fuzzy (CSF) information. These new approaches include the CSF Aczel-Alsina weighted average (CSFAWA) operator, and the CSF Aczel-Alsina ordered weighted average (CSFOWA) operator. In addition to this, we also introduce a list of novel techniques by making use of the theory of Aczel-Alsina aggregation tools such as CSF Aczel-Alsina weighted geometric (CSFAWG) and CSF Aczel-Alsina ordered weighted geometric (CSFOWG) operators. To demonstrate the resilience and efficacy of the approaches that have been mentioned, we will examine a few exceptional examples and remarkable properties of the methodology that we have devised. In addition, a characterization is provided for an approach to the MCDM issue using the CPF information system. We use the example of electric automobiles as a case study to illustrate the uniformity and dependability of the methodology that we have established. This example was chosen because of the high cost of fuel and the present economic challenges that are being encountered by families in the middle class. An empirical case study is also constructed to determine an electric car that is desirable based on the techniques that we have proposed. To evaluate the correctness and superiority of the established strategies, we compare the outcomes of previously used techniques with the AOs currently being provided.

Strategies for Enhancing Industry 4.0 Adoption in East Africa: An Integrated Spherical Fuzzy SWARA-WASPAS Approach

Strategies for Enhancing Industry 4.0 Adoption in East Africa: An Integrated Spherical Fuzzy SWARA-WASPAS Approach

Interval-valued spherical fuzzy MABAC method based on Dombi aggregation operators with unknown attribute weights to select plastic waste management process

The widespread use of plastic products worldwide generates an enormous amount of waste. Plastic is a substance that is not biodegradable and is permanent in the environment. The environment and living beings are negatively affected by this waste if it is not managed properly. However, the assessment and selection of effective plastic waste management methods is a complex and uncertain decision-making problem due to the involvement of multiple conflicting attributes, the imprecise human mind, and a lack of information. Recently, interval-valued spherical fuzzy (IVSF) sets have been recognized as one of the suitable tools to handle vague information. In this paper, we introduce a hybrid multi-attribute group decision-making methodology based on the entropy method, deviation-based method, and Multi-Attribute Border Approximation area Comparison (MABAC) method with IVSF sets to choose the most effective plastic waste management process in which the decision experts’ and attribute weights are completely unknown. In this model, the entropy and deviation-based methods are utilized to calculate the decision experts’ and attribute weights, respectively. Also, the MABAC method is used to evaluate the priority order of the plastic waste management options. To do this, Dombi weighted averaging and Dombi weighted geometric operators are developed in the IVSF environment. In the proposed model, the Dombi weighted averaging operator is used to fuse several decision experts’ information, and the Dombi weighted geometric operator is used to determine the border approximation area matrix. Then, to confirm the applicability of the suggested model, we look at a numerical example of choosing the most effective method for managing plastic waste with IVSF information. In the numerical example, we consider six alternatives and four important attributes with ten sub-attributes by consulting four decision experts. The result of this study shows that ‘Recycling (A2)’ is the most effective method to reduce plastic waste. Finally, we compare the proposed method with the existing ones to demonstrate its validity.

A hybrid decision making support method for parcel lockers location selection

Due to the rise of e-commerce, there has been a significant increase in commercial transactions, playing a crucial role in driving economic growth. However, the delivery systems need help locating addresses and dealing with issues such as missed deliveries and exacerbating problems in last-mile logistics, such as traffic congestion and environmental impact. Parcel lockers offer an efficient solution to address these critical issues, but selecting an appropriate location is vital to ensure optimal service and improve overall logistic performance. For this motive, our work aims to define the best location for parcel lockers in Ireland, Dublin, using the Spherical Fuzzy Analytic Hierarchy Process (SFAHP). Spherical Fuzzy Sets (SFS) involve decision-makers hesitating in evaluating location selection. The integrated model is a suitable approach to avoid AHP deterministic disadvantages. Moreover, it is the first application of SFAHP to select parcel locker locations. The obtained results will benefit policymakers in making their strategic decisions on selecting parcel locker locations.

Evaluation of economic development policies using a spherical fuzzy extended TODIM model with Z̆-numbers.

Zadeh's Z̆-numbers are able to more effectively characterize uncertain information. Combined with "constraint" and "reliability". It is more powerful at expressing human knowledge. While the reliability of data can have a direct impact on the precision of decisions. The key challenge in solving a Z̆-number issue is reasoning about both fuzzy and probabilistic uncertainty. Existing research on the Z̆-number measure is only some, and most studies cannot adequately convey the benefits of Z̆-information and the properties of Z̆-number. Considering this study void, this work concurrently investigated the randomness and fuzziness of Z̆-number with Spherical fuzzy sets. We first introduced the spherical fuzzy Z-numbers (SFZNs), whose elements are pairwise comparisons of the decision-maker's options. It can be used effectively to make true ambiguous judgments, reflecting the fuzzy nature, flexibility, and applicability of decision making data. We developed the operational laws and aggregation operators such as the weighted averaging operator, the ordered weighted averaging operator, the hybrid averaging operator, the weighted geometric operator, the ordered weighted geometric operator, and the hybrid geometric operator for SFZ̆Ns. Furthermore, two algorithm are developed to tackle the uncertain information in the form of spherical fuzzy Z̆-numbers based to the proposed aggregation operators and TODIM methodology. Finally, we developed the relative comparison and discussion analysis to show the practicability and efficacy of the suggested operators and approach.

Bus type selection with fuzzy approach for public transportation

There is tightening political pressure on cities to publish zero-emission strategies to decrease greenhouse emissions. To achieve these targets, decreasing public transportation emissions has become critical. There are different types of green transportation such as electric, compressed natural gas, hydrogen, biofuel, etc. This study develops a model regarding a holistic view that not only focuses on economic and operational conditions but also on business and strategy to decide the best bus type for public transportation for Istanbul metropolitan area. To handle the vagueness and complexity of the problem, the Spherical Fuzzy AHP method is applied to the model, as the method can handle three membership functions, which are membership, non-membership, and hesitancy. Also, to compare the results a classical AHP is performed with the same data. Results show that the diesel bus type stands out as the best option for both methods regarding the chosen criteria for Istanbul. The others varied with respect to methods. This study sheds light on results that could vary regarding the country’s context such as economic, social, and political factors. Although there are lots of studies on vehicle selection problems by applying multi-criteria decision-making methods, many of them have not utilized Spherical Fuzzy Set. To test the proposed model, a real case study is conducted. From this point, this study will not only contribute to the literature but also inform decision-makers and practitioners in terms of prioritizing their selection criteria.

A Proposed Approach to Evaluate Digital Business Model Selection for SuperApps using Interval Valued Spherical Fuzzy AHP

Various users have used SuperApps due to the rapid development of digital platforms. Due to their fast market entry by technical rivals and significant growth potential, SuperApps have become enterprises' preferred business method. SuperApps are the correct business, but senior managers must be careful when choosing which digital business models to employ. By classifying the digital management elements of SuperApps and comparing them to potential alternatives based on the preferences of eight digital leaders, we aimed to propose a method for choosing a suitable digital business model. Interval Valued Spherical Fuzzy Analytic Hierarchy Process (IVSF AHP) helps by giving decision-makers access to a broad range of preference domains. According to the rule, Spherical Fuzzy Sets adhere to the squared sum of the membership, non-membership, and hesitation degrees should fall within the range [0, 1]. Each element is distinct since it has an independent assignment within the same range. The IVSF AHP approach favored due to the complexity of the features of the digital business model and their transitional structure, is applied. The chosen digital business model may alter not only the managerial dynamics but also the revenue model of SuperApps depending on the sort of structural interaction of their platform network, according to the numerical application's results.

A two-stage MCDM model for reverse logistics network design of waste batteries in Turkey

Inadequate environmental resources and overpopulation reveal the need to protect and recover natural resources attentively. In this sense, the reverse logistics concept emerged as a key solution since it deals with product flow from the final user to the origin. There are various items that need to be considered in well-planned reverse logistics network designs and one of these items is batteries which include hazardous and precious materials in it. Hence, waste management of batteries via recycling becomes a very significant issue from both economic and environmental benefits. Accordingly, depending on the importance of the topic, a two-stage methodology is proposed in this study for providing a network design under multiple objectives. Within the first stage, the importance weights of objectives are obtained via Spherical Fuzzy Analytical Hierarchy Process (SF-AHP) and they are found as 0.248 for cost minimization, 0.3 for carbon emission minimization, 0.256 for employment rate maximization and 0.196 for development rate maximization. Afterward, in the second stage, a Multi-Objective Mixed Integer Linear Programming Model (MO-MILP) is developed to design the reverse logistics network and an application is performed in Turkey for validation. The model is solved for various scenarios including different quantities to be collected. Hence, it is obtained that the satisfaction degrees for employment and development objectives are 100% in all of the scenarios. However, the satisfaction degree of carbon emission minimization is around 96% and the less satisfied objective is the cost minimization having a satisfaction degree of 75% on average.

New Horizons in Bank Mergers: A Quantum Spherical Fuzzy Decision-Making Framework for Analyzing Islamic and Conventional Bank Mergers and Enhancing Resilience

This study explores the implications of merging two fundamentally different types of banks: Islamic and conventional banks. The research aims to provide insight into the unique opportunities and challenges presented by such a merger and to offer strategic guidance for future mergers. A balanced scorecard-based strategic analysis using a Quantum Spherical Fuzzy Decision-Making Approach was used to develop short- and long-term strategic plans for the merged bank. The balanced scorecard included 12 key performance indicators (KPIs) in 4 groups, and the methodology incorporated several questions to guide the analysis. The results of the study offer valuable insights into the potential opportunities and challenges of merging these two types of banks, as well as strategic recommendations for stakeholders at all levels. The study serves as a useful guideline for future mergers between similar or different types of banks. Overall, the findings suggest that a well-planned merger strategy is essential for avoiding challenges and maximizing the benefits of merging Islamic and conventional banks. By integrating the strengths of both types of banks, a merged entity could create a competitive advantage and potentially improve financial performance. However, this requires careful consideration of cultural differences, regulatory challenges, and other factors that could impact on the success of the merger.

A decision modeling approach for smart e-tourism data management applications based on spherical fuzzy rough environment

The technology deployment in smart e-tourism brings high potential in terms of customer data, events, reservations, and others. It acts as an effective and personalized guide to aid travelers. There is an increasing variety of smart e-tourism apps with multiple categories and criteria, but in terms of decision making, this presents a multicriteria complex problem to determine the best app from a group of available options with high criteria subjectivity. Literature reviews have evaluated and modeled the existing smart e-tourism apps alternatives, but informational uncertainty remains. The fuzzy sets and Multi-Attribute Decision Analysis (MADA) were used to handle the subjectivity issue. However, this process includes levels of uncertainty, which affects the decisions made and still an open issues. Spherical fuzzy rough sets (SFRSs) environment are useful in this situation for resolving fuzziness and ambiguity. This paper proposed a decision modeling approach for smart E-Tourism data management applications based on SFRSs environment. For methodology: firstly, a decision matrix is adopted for 5 different categories of Smart E-tourism’s system applications on the basis of the integrated 12 evaluation criteria. Secondly, a new formulation and development formulating a new extension of FWZIC, called a Spherical Fuzzy Rough-Weighted Zero-Inconsistency (SFR-WZIC), for weighting the smart key concept attributes involved in modeling smart e-tourism, whereas a new formulation and development for a new extension of FDOSM, called a Spherical Fuzzy Rough Decision by Opinion Score Method (SFR-DOSM), for modeling the applications of smart e-tourism per each e-tourism category; then, the new developments are integrated. The proposed methods were evaluated using systematic ranking and sensitivity analysis.

From risks to rewards: A comprehensive guide to sustainable investment decisions in renewable energy using a hybrid facial expression-based fuzzy decision-making approach

There are some risks in renewable energy investments, such as legal, technology and financial issues. Hence, appropriate actions should be taken to minimize these risks. However, each of the measures to be taken for the management of risks creates new costs for businesses. Therefore, to ensure the financial sustainability of the projects, measures for the most important risks should be taken at the first stage. Because of this situation, it is vital to make a priority analysis for the risks faced by renewable energy projects so that it can be possible to increase the effectiveness of risk management. Accordingly, in this study, it is aimed to examine the risks and rewards regarding sustainable investment decisions for renewable energy projects. In this scope, a novel model is generated by integrating different techniques. In this process, the evaluations of six different experts are taken into consideration. First, missing evaluations for the sustainable investment decisions in renewable energy are estimated with neuro decision-making and collaborative filtering. Secondly, the weights of the risk factors of sustainable energy investments are computed with neuro quantum spherical fuzzy (QNSLF) DEMATEL with golden cut. Thirdly, reward alternatives for sustainable decision making are analyzed with Neuro QNSLF TOPSIS with golden cut. This study contributes to literature by determining the most important risks for renewable energy projects by an original decision-making model. Another important novelty of this study is that a new technique called neuro decision-making has also been developed. In this technique, the facial expressions of the experts who evaluate are taken into consideration. It is defined that technological changes have the greatest significance. Additionally, governmental incentives are found as the most essential reward to improve sustainable investments in renewable energy. Thus, for the effective management of these risks, appropriate actions should be taken. It is also obvious that the competitiveness of companies that fall behind this new technology will decrease. In this context, these enterprises need to take the necessary measures to manage the technology risk to be sustainable in the long term.

Performance-emission optimization in a single cylinder CI-engine with diesel hydrogen dual fuel: A spherical fuzzy MARCOS MCGDM based Type-3 fuzzy logic approach

This paper presents a novel approach to optimize the performance and emission characteristics of a single cylinder compression ignition engine using diesel-hydrogen dual fuel. A TMI (timed manifold injection) system was designed employing an ECU (electronic control unit) for hydrogen induction into the engine manifold. The results showed a significant enhancement in BTHE (12.44% Max. enhancement at 85% full load condition under DH4 strategy) compared to base-diesel operation. The NOx emissions were enhanced to a maximum of 10.33 g/kw-hr at full load under the DH4 strategy. The emissions of UHC were found to be higher at lower loads and get significantly reduced to a maximum of 3.98 g/kw-hr at full load under the DH2 strategy. In comparison, soot emissions decrease substantially and are reduced to a maximum of 0.02 g/kw-hr at 85% full load condition under the DH5 strategy. The proposed method utilizes a Spherical Fuzzy MARCOS MCGDM-based Type-3 Fuzzy Logic approach, which integrates several criteria and uncertain inputs to improve decision-making. The paper outlines the theoretical framework of the approach and the experimental setup used for validation. The results demonstrate that the proposed method significantly reduces emissions while simultaneously improving the engine's performance. Overall, this study offers an innovative and effective solution for optimizing the performance and emissions of diesel-hydrogen dual fuel engines.

Sustainable resilient supplier selection for IoT implementation based on the integrated BWM and TRUST under spherical fuzzy sets

Supplier selection process plays a vital role in supply chain management and is the most important variable in its success. With increasing environmental considerations, organizations must consider sustainability considerations and economic goals to protect the environment. Furthermore, the destructive effects of disruptions on the supply chain performance of companies have prompted organizational experts to pay special attention to the concept of resilience. This study developed an integrated approach based on the extended version of Multi-Criteria Decision-Making (MCDM) methods in a spherical fuzzy (SFS) environment to address sustainable and resilient IoT supplier selection. In the proposed approach, the main criteria (i.e., resilience, and sustainability) have been used in the supplier selection process. Then, these criteria are weighted using the developed SFS-Best-Worst Method (BWM), which reduces uncertainty in pairwise comparisons. In the next step, the 14 selected IoT suppliers are evaluated and prioritized by applying SFS-mulTi-noRmalization mUlti-Distance aSsessmenT (TRUST) that considers a multi-normalization algorithm to reduce subjectivity in normalized data. The results of this study shows that the pollution control and risk-taking sub-criteria are placed in the first and second priorities, respectively. The comparison of the results of the SFS-TRUST with other MCDM methods and sensitivity analysis demonstrates the performance of the proposed approach and its ranking stability in various scenarios.

Einstein exponential operation laws of spherical fuzzy sets and aggregation operators in decision making.

The spherical fuzzy set (SFS) model is one of the newly developed extensions of fuzzy sets (FS) for the purpose of dealing with uncertainty or vagueness in decision making. The aim of this paper is to define new exponential and Einstein exponential operational laws for spherical fuzzy sets and their corresponding aggregation operators. We introduce the operational laws for exponential and Einstein exponential SFSs in which the base values are crisp numbers and the exponents (weights) are spherical fuzzy numbers. Some of the properties and characteristics of the proposed operations are then discussed. Based on these operational laws, some new aggregation operators for the SFS model, namely Spherical Fuzzy Weighted Exponential Averaging (SFWEA) and Spherical Fuzzy Einstein Weighted Exponential Averaging (SFEWEA) operators are introduced. Finally, a decision-making algorithm based on these newly introduced aggregation operators is proposed and applied to a multi-criteria decision making (MCDM) problem related to ranking different types of psychotherapy.

Integrating Spherical Fuzzy Sets and the Objective Weights Consideration of Risk Factors for Handling Risk-Ranking Issues

Risk assessments and risk prioritizations are crucial aspects of new product design before a product is launched into the market. Risk-ranking issues involve the information that is considered for the evaluation and objective weighting considerations of the evaluation factors that are presented by the data. However, typical risk-ranking methods cannot effectively grasp a comprehensive evaluation of this information and ignore the objective weight considerations of the risk factors, leading to inappropriate evaluation results. For a more accurate ranking result of the failure mode risk, this study proposes a novel, flexible risk-ranking approach that integrates spherical fuzzy sets and the objective weight considerations of the risk factors to process the risk-ranking issues. In the numerical case validation, a new product design risk assessment of electronic equipment was used as a numerically validated case, and the simulation results were compared with the risk priority number (RPN) method, improved risk priority number (IRPN) method, intuitionistic fuzzy weighted average (IFWA) method, and spherical weighted arithmetic average (SWAA) method. The test outcomes that were confirmed showed that the proposed novel, flexible risk-ranking approach could effectively grasp the comprehensive evaluation information and provide a more accurate ranking of the failure mode risk.

An advanced framework for leakage risk assessment of hydrogen refueling stations using interval-valued spherical fuzzy sets (IV-SFS)

The extensive population growth calls for substantial studies on sustainable development in urban areas. Thus, it is vital for cities to be resilient to new situations and adequately manage the changes. Investing in renewable and green energy, including high-tech hydrogen infrastructure, is crucial for sustainable economic progress and for preserving environmental quality. However, implementing new technology needs an effective and efficient risk assessment investigation to minimize the risk to an acceptable level or ALARP (As low as reasonably practicable). The present study proposes an advanced decision-making framework to manage the risk of hydrogen refueling station leakage by adopting the Bow-tie analysis and Interval-Value Spherical Fuzzy Sets to properly deal with the subjectivity of the risk assessment process. The outcomes of the case study illustrate the causality of hydrogen refueling stations' undesired events and enhance the decision-maker's thoughts about risk management under uncertainty. According to the findings, jet fire is a more likely accident in the case of liquid hydrogen leakage. Furthermore, equipment failure has been recognized as the most likely cause of hydrogen leakage. Thus, in order to maintain the reliability of liquid hydrogen refueling stations, it is crucial that decision-makers develop a trustworthy safety management system that integrates a variety of risk mitigation measures including asset management strategies.

The role of Society 5.0 in achieving sustainable development: a spherical fuzzy set approach.

Society 5.0 promotes the use of artificial intelligence in human life and the return of humanity to the center of the world. Society 5.0 seeks to achieve economic growth while overcoming social and environmental challenges, contributing to the welfare of the global community. The purpose of this study is to explore how digital transformations introduced by Society 5.0 can contribute to the realization of sustainable development? To answer this question, the study primarily used the systematic literature review method to identify the dimensions and indicators that would quantify the role of Society 5.0 in achieving sustainable development. Then, the study utilized the total interpretive structural modeling (TISM) method to construct the conceptual model. Through spherical fuzzy analytical hierarchy process (SF-AHP) and spherical fuzzy decision-making trial and evaluation laboratory (SF-DEMATEL), the importance and influence of the indicators were determined. The results revealed that the most important indicators were "super-smart society" and "implementing circular economy to decrease environmental waste." The novelty of this research can be found in its application of the spherical fuzzy approach to examine the impacts of Society 5.0 smart technologies on achieving sustainable development, by addressing five major dimensions (governmental, economic, social, environmental, and technological). The findings could help managers to more effectively respond to the challenges of sustainable development by relying on Society 5.0.

Maclaurin Symmetric Mean Aggregation Operators Based on Spherical Fuzzy Information and Application to Decision-Making

In contemporary information fusion theory, the Maclaurin symmetric mean (MSM) operator is a traditional mean type aggregation operator (AO) that is an appropriate-able technique for aggregating numerical quantities. The MSM operator’s ability to record the relationships between the several input arguments is one of its standout features. The spherical fuzzy set (SFS) is also a remarkable technique that covers the maximum information from real-life scenarios with the help of four grades. This manuscript consists of the development of the MSM and weighted MSM for the information obtained by SFS. Consequently, the spherical fuzzy MSM (SFMSM) and spherical fuzzy weighted MSM (SFWMSM) operators are developed, and their basic properties are studied. Finally, the developed SFMSM and SFWMSM operators have been applied to the real-life problem of the multi-attribute decision-making problem. All the results are compared and then clearly tabulated and graphed.

A multi-criteria decision-making approach for portfolio selection by using an automatic spherical fuzzy AHP algorithm

Portfolio selection for Stock evaluation and selection by an investor is multi-criteria decision-making (MCDM) problem of finding the best portfolio among an efficient set of portfolios, which should be tackled by using the appropriate techniques. The Analytic Hierarchy Process (AHP) is amongst the most widely used MCDM methods, which is often used in operation management. The main feature of AHP is, that, it firstly reduces the complex decision problems in hierarchical structures of objectives, criteria, sub-criteria, and alternatives and then, uses a fundamental scale to construct pairwise comparisons. The Spherical Fuzzy Sets (SFS) have many advantages in handling the uncertainty and vagueness of ordinary and 2D Fuzzy Sets (FS)s. Therefore, taking the advantage of AHP and SFSs in this paper, we modify the Fuzzy Analytic Hierarchy Process (FAHP) into Spherical fuzzy AHP (SFAHP). We introduce the concept of Spherical Fuzzy Preference Relation (SFPR) and develop an automatic algorithm to construct a consistent SFPR from an inconsistent one. The validity of the proposed approach is tested through an illustrative application of portfolio selection on the Pakistan Stock Exchange to make a prototype of our results.