Evaluation Based On Distance From Average Solution Research Articles

Incorporating failure mode and effects analysis into a novel framework for hydrogen production from solid waste gasification

Gasifying waste represents a sustainable and highly effective approach; however, ensuring rigorous control of hydrogen leakage is paramount to guarantee both safety and long-term sustainability. Due to the distinctive features of these production facilities and the likelihood of their placement in public municipal spaces, it is imperative to prioritize a comprehensive approach to ensuring the safety of these installations. This includes a thorough evaluation of the risks linked to hydrogen and taking proactive measures to prevent accidents, a crucial aspect that has been neglected in prior research endeavors. Therefore, this article introduces an enhanced iteration of the risk management framework based on the failure mode and effects analysis (FMEA) and the evaluation based on distance from average solution (EDAS) methods, implemented in a municipal solid waste gasification system to facilitate hydrogen production. The research employs FMEA to scrutinize potential failure modes, strategically prioritizing them through advancements in the EDAS methodology. Notably, this framework is seamlessly integrated during the conceptual design phase, showcasing its efficacy in bolstering risk-informed design strategies. Through rigorous comparative and sensitivity analyses, the resilience of the framework is underscored. The refined FMEA-EDAS framework holds substantial practical implications for managing hydrogen production facilities by providing a structured approach to resource allocation and ensuring adherence to industry standards. Furthermore, it fosters interdisciplinary collaboration, potentially serving as a knowledge hub to fortify safety measures within the realm of hydrogen production.

Development of RAMDOE: a new method for rapidly ranking alternatives with supplementary options and considering changes in criteria values

This paper delves into the development and validation of the RAMDOE method, a pioneering approach in multi-criteria decision making (MCDM) that seamlessly integrates the root assessment method (RAM) and design of experiments (DOE) techniques, addressing the inflexibility of traditional MCDM methods in accommodating adjustments in criteria ranges and the addition of new alternatives without necessitating a complete overhaul of the decision framework. Through empirical analysis, the study demonstrates the RAMDOE method's remarkable efficacy in precisely ranking alternatives, as illustrated through a practical case study focused on the selection of a supplier from a pool of seven candidates. One of the most notable aspects of the RAMDOE method lies in its capacity to formulate a regression equation that accurately captures the intricate relationship between alternative scores and criteria values, enabling decision-makers to seamlessly integrate new alternatives into the decision-making process without the cumbersome task of recalibration, thereby distinguishing it from conventional MCDM techniques such as TOPSIS (technique for order of preference by similarity to ideal solution), COPRAS (complex proportional assessment), MOORA (multiobjective optimization on the basis of ratio analysis), EDAS (evaluation based on distance from average solution) and CODAS (combinative distance-based assessment). The practical implications of these findings are profound, offering decision-makers across various domains a more efficient and adaptable framework to navigate complex decision scenarios. Particularly in contexts like supplier selection, where criteria ranges may vary significantly, the RAMDOE method provides decision-makers with a robust toolset to make informed decisions, presenting a promising avenue for addressing the dynamic nature of decision-making environments and enhancing the overall robustness and flexibility of MCDM processes in real-world applications

Extended EDAS Analysis for Multi-Criteria Decision-Making Based on Distributed Generation (DG) Technologies System

Recently, there has been a growing interest in distributed generation (DG) technologies, driven by various factors such as fuel price uncertainties, environmental constraints, and increasing power consumption along with transmission capacity shortages, in modern power systems. DG, which involves utilizing clean and renewable energy sources for power generation within the distribution system, has gained significant attention globally. Many developing countries, including Libya, are considering the adoption of DG technologies as part of their energy system expansion plans. Libya, located in North Africa and characterized by vast desert lands, has abundant solar radiation, making solar energy a promising and sustainable source of power. However, despite this energy potential, the southern part of Libya faces frequent power outages. In order to effectively maintain service quality, it is essential to conduct quantitative evaluation of wireless sensor networks. the evaluation of wireless sensor networks involves addressing the multiple attribute group decision-making (MAGDM) problem. To tackle the challenges of MAGDM, an extension of the classical EDAS (Evaluation based on Distance from Average Solution) method is proposed in this paper. The proposed method incorporates interval-valued intuitionistic fuzzy sets (IVIFSs), which provide a more flexible and comprehensive representation of uncertainty, to handle the complexities of MAGDM. The paper begins with a brief review of essential concepts related to IVIFSs. Then, the weights of attributes are determined using the CRITIC method. Subsequently, the IVIF-EDAS method is established by integrating the EDAS method with IVIFSs, and all the calculation procedures are described.

Enterprise technological innovation capability evaluation using a spherical fuzzy number based CSM-EDAS model

With the rapid development of science and technology, the flow of information has become more convenient, and society has entered the era of knowledge economy. In this era, technological innovation capability is becoming increasingly important and has become an important weapon for enterprises to survive in fierce competition, especially for technology-based small and medium-sized enterprises. Nowadays, technology-based small and medium-sized enterprises have developed many technological innovation achievements through continuous technological innovation, and have created a large number of high-tech products and services. Technological innovation has been proven to effectively improve the core competitiveness and economic benefits of technology-based small and medium-sized enterprises. Therefore, evaluating the technological innovation capabilities of technology-based small and medium-sized enterprises has both theoretical and practical significance. The enterprise technological innovation capability evaluation from a low carbon perspective could be deemed as the multiple attribute group decision making (MAGDM) problem. Recently, the evaluation based on distance from average solution (EDAS) technique and cosine similarity measure (CSM) technique has been employed to manage MAGDM issues. The spherical fuzzy sets (SFSs) are used as an efficient tool for portraying uncertain information during the enterprise technological innovation capability evaluation from a low carbon perspective. In this paper, the spherical fuzzy number EDAS based on the CSM (SFN-CSM-EDAS) technique is cultivated to manage the MAGDM under SFSs. Finally, a numerical study for enterprise technological innovation capability evaluation from a low carbon perspective is supplied to validate the proposed technique. The main contributions of this paper are outlined: (1) the EDAS and CSM technique was extended to SFSs; (2) the CRITIC technique is used to derive weight based on CSM technique under SFSs. (3) the SFN-CSM-EDAS technique is founded to manage the MAGDM under SFSs; (4) a numerical case study for enterprise technological innovation capability evaluation from a low carbon perspective and some comparative analysis is supplied to validate the SFN-CSM-EDAS technique.

A 2TLNS-based exponential TODIM-EDAS approach for evaluating sustainable development of cross-border e-commerce platforms under uncertainty

In the context of globalization, cross-border e-commerce platforms have become the main way for enterprises to achieve international trade transformation and overseas investment. From this, it can be seen that cross-border e-commerce platforms are of great importance to the development of enterprises, and the development of cross-border e-commerce platforms is also a necessary choice for the development of the times. In the new era, in order to make cross-border e-commerce platforms better serve enterprises and bring economic benefits to their development. The sustainable development capability evaluation of third-party cross-border e-commerce (TPCBEC) platform is a MAGDM. Recently, the Exponential TODIM (ExpTODIM) technique and Evaluation Based on Distance from Average Solution (EDAS) technique has been employed to cope with MAGDM issues. The 2-tuple linguistic neutrosophic sets (2TLNSs) are employed as a tool for portraying uncertain information during the sustainable development capability evaluation of TPCBEC platform. In this paper, the 2-tuple linguistic neutrosophic number Exponential TODIM-EDAS (2TLNN-ExpTODIM-EDAS) technique is implemented to manage the MAGDM under 2TLNSs. Finally, a numerical study for sustainable development capability evaluation of TPCBEC platform is constructed to validate the implemented technique. Thus, the main advantages of the proposed 2TLNN-ExpTODIM-EDAS technique are outlined: (1) the proposed 2TLNN-ExpTODIM-EDAS technique not only handles the distances information from the 2TLNNAS, but also portrays the DMs’ psychological behavior during the sustainable development capability evaluation of TPCBEC platform. (2) the proposed 2TLNN-ExpTODIM-EDAS technique analyze the behavior of the TODIM technique and EDAS technique as MADM techniques when they are hybridized.

Evaluating the Performance of Railway Transportation Companies Using Multi-Criteria Decision-Making Methods

The purpose of performance evaluation is to generate measurable data on an organization's performance, with the goal of assisting managerial decision-making and enhancing overall performance. In this study, the key performance indicators (KPIs) for railway transportation companies are identified based on expert opinions and previous frameworks. The operational performance of various railway freight transport companies was evaluated using multi-criteria decision-making methods (MCDM). Among the MCDM approaches, the Evaluation Based on Distance from Average Solution (EDAS) method was applied as the main method. In addition to the EDAS method, alternative MCDM methods such as TOPSIS, PROMETHEE II, and COPRAS were used to highlight potential deviations when compared to the results obtained with the EDAS method. Based on the research findings, three out of the seven KPIs, namely safety, have the highest weight at 38%, followed by punctuality at 19%, and journey time at 12%. Subsequently, companies were ranked according to their performance based on all KPIs. Furthermore, a sensitivity analysis was conducted to demonstrate how changes in the relative weights of KPIs can affect the results.

A Cloud Model-Based CRITIC-EDAS Decision-Making Approach with Linguistic Information for Marine Ranching Site Selection

Modern marine ranching construction has drawn growing attention of relevant planning authorities and enterprises with the potential value of oceans becoming apparent. To satisfy the demand for a successful marine ranching construction, site selection is considered as the first and fundamental procedure. This work aims to help planning authorities find the optimal marine ranching site by introducing a methodological evaluation framework for solving this critical problem. Firstly, the advanced CRiteria Importance Through Inter-criteria Correlation (CRITIC) method is extended by using a cloud model to determine the relative importance of attributes in marine ranching site selection problems. Secondly, the Evaluation based on Distance from Average Solution (EDAS) method is developed by integration with the cloud model to obtain the ranks of alternative sites for marine ranching construction. The proposed cloud model-based CRITIC-EDAS method considers the fuzziness and randomness of the linguistic terms given by experts simultaneously to ensure the scientificity and rationality of decision making. Finally, a real-world marine ranching site selection problem is solved by using the proposed model, where the efficiency and reliability of the proposed model are verified according to the comparison with other traditional multi-attribute decision-making methods.

Evaluation of digital commercial bank security under uncertainty: A multiphase approach based on intuitionistic fuzzy CRITIC and EDAS framework

Currently, the digital economy continues to deepen its development, and it has become a consensus among all sectors as the direction of global future development. Digital finance, as a fleet in the wave of digital economy, is rapidly heading towards the sunny shore of benefiting the public and serving entities driven by the digital technology engine. Xinwang Bank is a fast boat in the digital finance fleet, always adhering to the principle of technology, building an open platform, and actively promoting the construction of an open, shared, and secure digital credit ecosystem from three levels: institutional, industry, and ecological, to assist in the development of the digital economy. The digital commercial bank security evaluation is a classical multiple attribute group decision making (MAGDM) problems. Recently, the Evaluation based on Distance from Average Solution (EDAS) method has been employed to manage MAGDM issues. The intuitionistic fuzzy sets (IFSs) are used as a tool for portraying uncertain information during the digital commercial bank security evaluation. In this paper, the intuitionistic fuzzy nunmber EDAS (IFN-EDAS) method is cultivated to manage the MAGDM based on Hamming distance and Euclidean distance under IFSs. In the end, a numerical case study for digital commercial bank security evaluation is supplied to validate the proposed method. The main contributions of this paper are outlined: (1) the EDAS method has been extended to IFSs based on Hamming distance and Euclidean distance; (2) the CRITIC method is used to derive weight based on Hamming distance and Euclidean distance under IFSs. (3) the IFN-EDAS method based on Hamming distance and Euclidean distance is founded to manage the MAGDM based on the Hamming distance and Euclidean distance under IFSs; (4) a numerical case study for digital commercial bank security evaluation and some comparative analysis is supplied to validate the proposed method.

Selection of a sustainable location for waste electrical and electronic equipment recycling plant using Entropy and Evaluation based on Distance from Average Solution.

The production and consumption of electronic goods have experienced a significant increase over the years, leading to a substantial surge in the global volume of electronic waste, commonly referred to as Waste Electrical and Electronic Equipment (WEEE). The selection of a sustainable location for WEEE recycling plants plays a crucial role in mitigating environmental concerns, preserving resources and promoting economic development. It signifies a proactive and responsible approach to electronic waste management in the contemporary world. To tackle the challenge of selecting sustainable locations for WEEE recycling plants, this study employed the Entropy and Entropy and Evaluation based on Distance from Average Solution (EDAS) methodologies, evaluating 10 alternative cities in Turkey based on 13 criteria. The selected criteria include land cost, personnel cost, energy cost, availability of labour, government support degree, tax preferences, road network accessibility, number of electronic equipment producers, existence of recycling plants, suitability of land use, population and availability of renewable resources (wind power and solar energy). The Entropy method was employed to calculate the weights assigned to each criterion, whereas the EDAS method was utilized to evaluate the decision alternatives. The results provide region-specific recommendations, such as Antalya for the Mediterranean region and Samsun for the Black Sea region. The literature lacks sufficient research on the selection of sustainable locations for WEEE recycling plants. Furthermore, the utilization of real data enhances the study's credibility and provides practical insights for decision-making. The selection of a sustainable location for a WEEE recycling plant in Turkey not only demonstrates the country's environmental commitment but also sets a global example for responsible waste management.

Prioritizing sustainable renewable energy systems in Tunisia: An integrated approach using hybrid multi-criteria decision analysis

In recent years, renewable energy technologies (RETs) have become increasingly popular worldwide to achieve energy sufficiency, reduce reliance on conventional fuels, and mitigate their devastating environmental impact. Nonetheless, more appears to have stayed the same in emerging economies, such as Tunisia, as various barriers hampered the implementation of these technologies. Hence, the prime objective of this article is to conduct a thoughtful assessment of four prominent renewable energy options for electricity generation and explore the most potential barriers hindering their development in Tunisia. To do so, a two-stage approach was applied. First, CRiteria Importance Through Inter-Criteria Correlation (CRITIC) and Evaluation based on Distance from Average Solution (EDAS) were used to evaluate the considered alternatives, namely solar PV, concentrated solar power (CSP), onshore wind, and biomass. Then, an integrated step-wise assessment ratio analysis and decision-making trial and evaluation laboratory approach (SWARA-DEMATEL) was developed to identify the most relevant barriers. The related criteria and barriers were determined based on an exhaustive literature review and experts’ feedback. The obtained results indicated that solar PV and wind were the most promising renewable technologies, while biomass was the worst option. To validate the outcome and demonstrate the effect of changing input data on the final results, a sensitivity analysis has been carried out. As for the key obstacles, political instability, high upfront costs, and market access mechanisms were the most influential barriers. Hence, prioritizing different RETs and analyzing the inherent barriers to their utilization would offer insightful guidance to policymakers, enabling them to establish efficient strategies for overcoming these obstacles, and accelerating the deployment of these technologies in the country.

Prioritization of sustainable approaches for smart waste management of automotive fuel cells of road freight vehicles using the q-rung orthopair fuzzy CRITIC-EDAS method

Fuel cell electric vehicles (FCEVs) are a contemporary technology that is making headway in the expanding automotive industry. To promote FCEV effectiveness, environmentally acceptable limits need to be considered during their whole life cycle. End-of-life automotive fuel cells (AFCs) are one of the major contemporary challenges facing the sustainable business of transportation companies. The paper introduces a hybrid q-rung orthopair fuzzy (q-ROF)-based methodology to handle uncertainties and vagueness. It couples and extends the criteria importance through intercriteria correlation (CRITIC) and evaluation based on distance from average solution (EDAS) methods with q-ROF sets. This research aims to provide essential methodological and practical frameworks, as well as guidelines for improving the effectiveness of engaged FCEVs in transportation companies. The q-ROF CRITIC-EDAS methodology provides a systematic method for prioritizing sustainable approaches for smart waste management of AFCs of road freight vehicles. The incorporation of the real-life case study demonstrates its practical applicability and validity. The introduced q-ROF CRITIC-EDAS model could be extensively applied to the AFC waste management in order to assist stakeholders in making decisions consistent with the sustainability objectives.

Exploring the critical factors affecting the adoption of blockchain: Taiwan’s banking industry

As an emerging technology, blockchain has recently gained attention in both academic and economic fields, but its adoption is not yet widespread in the banking sector in Taiwan. As academics have paid scant attention to this topic, this study determines the critical factors affecting blockchain adoption from the organizational perspective in the banking industry. We propose hybrid methods to fill the gap in the literature. First, we apply the technology-organization-environment framework as the basis and combine relevant factors as a framework to identify the relevant evaluation factors. Second, we propose a hybrid method that integrates the decision-making trial and evaluation laboratory (DEMATEL) with the evaluation based on distance from average solution (EDAS) approach and employs DEMATEL to measure the importance of the factors and alternatives to blockchain as ranked by the EDAS method. According to the ranking results, we identify the best preference among alternatives to blockchain. The results suggest that organizational and technological aspects are the main considerations to enhance and promote the effectiveness of blockchain adoption. This study suggests valuable strategies for stimulating blockchain adoption in the banking sector in Taiwan.

Graph model for conflict resolution based on the combination of probabilistic uncertain linguistic and EDAS method

The ranking of decision makers (DMs)’ preferences for feasible states in the graph model for conflict resolution (GMCR) is crucial for accurately determining stability results. This paper addresses the issue of subjective ranking methods lacking theoretical foundation and causing ambiguity when the number of feasible states is high by proposing the implementation of the multi-attribute decision-making (MADM) method in the GMCR. The paper utilizes the average level to choose evaluation based on distance from average solution (EDAS) method for determining the DM’s preference ranking, which can effectively reduce the impact of anomalous evaluations. Further, the PUL-EDAS method based on probabilistic uncertainty linguistics (PUL) is developed, which overcomes the shortcomings of the traditional EDAS method, which only applies to the simple evaluation of information. The PUL aligns with DMs’ daily evaluation practice by providing an interval for the quality of qualitative linguistic evaluations. Furthermore, it utilizes an objective aggregation method to calculate comprehensive evaluation information from all DMs. In addition, the four fundamental stability definitions, applicable solely under crisp preferences, are extended to the PUL context, providing related extended definitions. Finally, to ensure the scientific validity and practicality of the proposed theory, this paper selects digital rural governance as the research context for conflict calculus analysis, comparing it with other MADM methods in the preference ranking section.

Corporate governance for sustainable development in Vietnam: Criteria for SOEs based on MCDM approach.

This research explores the nexus between corporate governance and sustainable development, focusing on State-Owned Enterprises (SOEs) in Vietnam. Recognizing the pivotal role of SOEs in the national economy, this study employs a Multi-Criteria Decision-Making approach (MCDM) to assess and enhance the corporate governance frameworks of these entities. First, the Data Envelopment Analysis (DEA) model is employed to identify the most qualified prospective SOEs firms based on several quantitative criteria. Then, the spherical fuzzy analytic hierarchy process (SF-AHP) model is used to identify priority weights for a given set of qualitative criteria, the Evaluation based on distance from average solution (EDAS) model is implemented to rank enterprises in the SOEs sector. To validate the proposed models, a case study conducted within the Vietnamese electric power industry is utilized. The MCDM methodology integrates diverse factors such as business management, corporate social responsibility, and corporate governance shareholder to construct a comprehensive evaluation framework. By applying this approach, the study aims to identify the key drivers and barriers influencing corporate governance practices within Vietnamese SOEs. The study's findings illustrate the efficacy of the suggested approach in evaluating corporate governance performance, providing valuable insights for policymakers, corporate leaders, and stakeholders involved in shaping the governance landscape of SOEs in Vietnam. By aligning corporate governance with sustainable development principles, the research aims to contribute to the ongoing discourse on responsible business practices, offering practical recommendations to enhance the performance and resilience of SOEs in the pursuit of long-term socio-economic and environmental sustainability.

Implementasi Metode EDAS Dalam Penilaian Kinerja Dosen Pada Masa Pandemi Covid-19 dengan Pembobotan Entropy

Along with the development of technology that makes online learning run well, but the enthusiasm for student learning is not like when face to face and there are still many students who do not take various courses so that students' knowledge abilities are greatly decreased. When online learning takes place, it is very necessary for a lecturer's performance to arouse students' enthusiasm in participating in online learning. Because during this pandemic the role of lecturers is very necessary to develop an innovation and be able to make students not bored in participating in online learning. And also in terms of the performance appraisal process, several problems often occur, namely the speed in the performance appraisal process and also the accuracy of the performance appraisal. In assessing the performance of lecturers during online learning, there are several criteria including Discipline, Delivery of Materials, Interaction, Discussion Questions and Answers and Punctuality. Based on these problems, a decision support system is needed as a problem solving technique and is assisted by a method that can produce an accurate final value. The method is the Evaluation Based On Distance From Average Solution (EDAS) and Entropy method which is very helpful in generating weight values ??from alternative data and criteria so as to get the final results obtained in Alternative L9 with a value of 0.31025 on behalf of Surya Darma Nst, M. Kom.

Tarım sigortaları ve doğal afetler: Türk tarım sigortaları havuzu (TARSİM) finansal performansının seçili kriterler dâhilinde değerlendirilmesi

Agriculture is closely linked to weather and climatic conditions, rendering it vulnerable to the impact of natural disasters. While such risks are inherent in agricultural activities, the escalation in both frequency and severity of these disasters in recent years can be attributed to the interplay of climate change, global warming, and ecological degradation. In this context, agricultural insurances offer financial assistance to farmers by extending insurance coverage to mitigate potential production failures stemming from these hazards. In Turkey, the insurances included in the Agricultural Insurance Pool (TARSIM) range from crop, greenhouse, and poultry, to drought yield insurances. In this study, the financial performance of TARSIM during the period 2018-2022 has been evaluated by using Criteria Importance Through Intercriteria Correlation (CRITIC) objective criteria weighting with Evaluation based on Distance from Average Solution (EDAS) and Multi-Atributive Ideal-Real Comparative Analysis (MAIRCA) multi-criteria decision-making (MCDM) techniques. The analyses included seven financial ratios based on eight indicators, and as a result, the criterion with the highest weight was determined as the Total Premiums Received-Equity ratio, and by considering all utilized methods, the first two years with the best financial performance was identified as 2018 and 2019.

Research on the interplay between green finance and manufacturing sustainability outcomes: insights for low-carbon economy in the post-COVID-19 era.

In the quest to strengthen resilient and sustainable recovery in the post-COVID-19 era, there is a huge requirement for manufacturing firms to adopt green finance which is dominated by green bond issuance. Nevertheless, published studies that provide insights on factors that influence the issuance of green bonds within manufacturing firms in the post-COVID-19 era and the impact on sustainable outcomes are currently non-existent. Therefore, this study analyzed the interrelationships that exist between the influencing factors of green bond issuance within manufacturing firms using decision-making trial and evaluation laboratory (DEMATEL) and data from Nigerian manufacturing firms. Then, a structural model of their importance levels was illustrated using interpretive structural modeling (ISM) while their impact on manufacturing sustainability outcomes was estimated with the aid of evaluation based on distance from average solution (EDAS). The study results highlight the key influencing factors of green bond issuance as environmental competencies, policy framing, low corruption, public awareness, and government support thereby signifying the criticality of strong institutions in facilitating green finance in the post-pandemic era. Besides, the study results demonstrate that green finance can significantly strengthen manufacturing sustainability in the post-COVID-19 era via green bonds by enhancing sustainable waste management, technological growth, and quality improvement as well as reducing carbon emissions. The study findings can provide a reference to decision-makers in manufacturing enterprises to predict scenarios and enact policies that facilitate the success of green finance in the post-COVID-19 era to further develop a low-carbon economy and increase competitive edge.

A Multi-criteria decision making approach for 3D printer nozzle material selection

Rapid advancements in 3D printing technology have compelled the manufacturers to search for better nozzle material in the extruder of 3D printers. Materials ranging from brass to tungsten carbide and ruby are primarily used as the nozzle material. In 3D printing technology, due to major constraints imposed by the filament material and other decisive factors, no single nozzle material satisfies all the desired characteristics for a real time application. Thus, it has become crucial to select the most appropriate nozzle material with the desired properties for enhanced 3D printing performance. In this paper, the performance of eight candidate nozzle materials is evaluated based on nine selection criteria. Entropy method is utilized to determine the criteria weights, whereas, evaluation based on distance from average solution (EDAS) method is employed to identify the best suited 3D printer nozzle material. Tungsten carbide emerges out as the best choice, followed by titanium alloy (TiAl6V4). This paper also proposes a sensitivity analysis to establish the robustness of the adopted methodology.

A comprehensive MAGDM-based approach using EDAS and CRITIC as an auxiliary tool for quality evaluation of ceramic product modeling design

Ceramic art has a long history of development in China and is an important component of the inheritance and development of traditional culture. The highly distinctive ceramic art expression content has been sought after by many international research enthusiasts and applied to product design, highlighting different social backgrounds and special cultural connotations of different eras, while also laying an important theoretical foundation for the inheritance and development of culture. The quality evaluation of ceramic product modeling design could be deemed as a classic multiple attribute group decision making (MAGDM) problem. Recently, the EDAS and CRITIC method has been used to cope with MAGDM issues. Spherical fuzzy sets (SFSs) can excavate the uncertainty and fuzziness in MAGDM more effectively and deeply. In this article, on basis of evaluation based on distance from average solution (EDAS), a novel spherical fuzzy number EDAS (SFN-EDAS) method based on Hamming distance and Euclid distance is built for dealing with MAGDM. Moreover, when the attribute weights are completely unknown, the CRITIC method is extended to SFSs to acquire the attribute weights. Finally, SFN-EDAS method is used for quality evaluation of ceramic product modeling design to prove practicability of the developed method and compare SFN-EDAS method with existing methods to further demonstrate its superiority.

An Integrated Neutrosophic Approach for the Urban Energy Internet Assessment under Sustainability Dimensions


 The urgent issue of climate change has resulted in an increasing preoccupation with the transition to low-carbon energy. The urban energy internet (UEI) enables the efficient utilization of renewable energy via the integration of contemporary energy grids, smart energy services, and cyber-physical systems. Consequently, the assessment of urban energy is vital for the construction of low-carbon cities. This study intends to provide an integrated decision-making approach for addressing assessment challenges related to UEI, with a focus on sustainability. The introduced approach adopts the opinions of three experts to express their opinions through semantic terms in evaluating sustainability factors and evaluating UEI projects. Determining the most suitable project for sustainable UEI is a difficult task. In addition, there are multiple sustainability dimensions, including: economic, social, technical, environmental and resource dimension. This paper presents an integrated approach through which experts can use semantic terms to express their opinions to evaluate the priorities of sustainability dimensions that affect the sustainability of UEI projects. Therefore, this study applies a hybrid multi-criteria decision making (MCDM) approach that takes into account multiple dimensions. Also, the uncertainty in the study is handled by type 2 neutrosophic numbers (T2NNs). Initially, the CRiteria Importance through Inter-criteria Correlation (CRITIC) method was used to determine the relative importance of the sustainability dimensions used in the study. Also, the evaluation based on distance from average solution (EDAS) method was used to rank the selected alternatives. The results indicate that the technical dimension is the most important with a weight of 0.384. Finally, a sensitivity analysis was conducted to prove the validity and reliability of the developed framework with differences in weights.