Evaluation Based On Distance From Average Solution Research Articles

Examining thedrivers of forest cover change and deforestation susceptibility in Northeast India using multicriteria decision-makingmodels.

The increasing rates of forest cover change and heightened vulnerability to deforestation present significant environmental challenges in Northeast India. This study investigates the dynamics of forest cover changeand susceptibility to deforestation in this region from 2001 to 2021, utilizing data from the Hansen Global Forest Change (HGFC) productonthe Google Earth Engine (GEE) platform. A suite of multicriteria decision-making (MCDM) models-including VlseKriterijumska optimizacija I Kompromisno Resenje (VIKOR), Simple Additive Weighting (SAW), Evaluation Based on Distance from Average Solution (EDAS), and Weighted Aggregates Sum Product Assessment (WASPAS)-was employed to assess changes in forest cover and deforestation susceptibility across varied zones. Multicollinearity tests confirmed the relevance of the factors influencing deforestation. Statistical validations, such as the Wilcoxon Signed Ranks Test, underscored the models' robustness, revealing statistically significant outcomes. Additionally, Receiver Operating Characteristic (ROC) curve and Area Under the Curve (AUC) analysis demonstrated the superior fit of the VIKOR model (AUC = 0.938) compared to SAW (AUC = 0.901), EDAS (AUC = 0.895), and WASPAS (AUC = 0.864) in predicting current deforestation susceptibility. Validation affirmed the reliability of all MCDM methods, with VIKOR displaying high sensitivity (True Positive Rate, TPR = 0.878) and optimal AUC (0.938). Correlation analyses among the models identified significant inter-relationships, notably a positive correlation between EDAS and SAW, and a negative correlation between VIKOR and SAW. The regions of Assam, Nagaland, Mizoram, and Arunachal Pradesh were identified as experiencing significant forest cover loss, indicating a pronounced susceptibility to future deforestation. These findings underscore the need for immediate intervention to address this critical environmental issue.

Intuitionistic Linguistic EDAS Method with New Score Function: Case Study on Evaluating Universities’ Innovation and Entrepreneurship Education

Intuitionistic linguistic numbers (ILNs) describe expert evaluation information by representing semantic assessment values and reflecting the confidence level and hesitation of decision-makers. ILNs are widely used to handle uncertain and incomplete information. The Evaluation Based on Distance from Average Solution (EDAS) method selects the optimal solution based on the distance of each alternative from the average solution, making it suitable for multi-attribute decision-making with conflicting attributes. This study proposes a new scoring function for ILNs and develops an evaluation method combining ILNs with EDAS (IL-EDAS). Experts’ evaluations of each alternative’s indices are expressed using ILNs, and the EDAS method ranks the alternatives to select the optimal solution. We apply this method to assess innovation and entrepreneurship education capabilities in universities, and compare the results with those from other methods to verify their applicability and practicality.

Enhanced EDAS methodology for multiple-criteria group decision analysis utilizing linguistic q-rung orthopair fuzzy hamacher aggregation operators

The linguistic q-rung orthopair fuzzy (LqROF\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$L^{q}ROF$$\\end{document}) set serves as a useful way of presenting uncertain information by offering more space for decision experts. In the present research, we first link the concepts of Hamacher t-norm and t-conorm with the frame of LqROF\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$L^{q}ROF$$\\end{document} numbers to develop and analyze the innovative LqROF\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$L^{q}ROF$$\\end{document} Hamacher operations. Then, following the proposed Hamacher’s norm operations, a series of aggregation operators including LqROF\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$L^{q}ROF$$\\end{document} weighted averaging, LqROF\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$L^{q}ROF$$\\end{document} ordered weighted averaging, LqROF\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$L^{q}ROF$$\\end{document} hybrid averaging, LqROF\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$L^{q}ROF$$\\end{document} weighted geometric, LqROF\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$L^{q}ROF$$\\end{document} ordered weighted geometric, LqROF\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$L^{q}ROF$$\\end{document} hybrid geometric operators are investigated. Some interesting aspects of these AOs are also presented. We further develop evaluation based on distance from average solution (EDAS) approach in light of the newly outlined concepts to cope with LqROF\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$L^{q}ROF$$\\end{document} decision-making problems where the weight information of criteria is fully unknown, ultimately, the practicality of the framed approach is demonstrated through an empirical case, and a detailed analysis is carried out to showcase the methodology dominance.

A new extension of the EDAS method in a fuzzy environment for group decision-making

The complexity of the decision-making problems being analysed has led to the development of multiple multi-criteria decision-making (MCDM) methods. One of the more recent methods belonging to this group is the evaluation based on distance from average solution (EDAS) method. To date, it has found extensive use in solving real-world decision-making problems and has seen many extensions to input data types other than real numbers. One of these is the EDAS method for group decision-making in a fuzzy environment. This method aggregates individual evaluations of decision-makers into a group evaluation using the arithmetic mean. This may result in equal group ratings despite the variety of individual ratings, making it difficult or even impossible to rank alternatives because the EDAS algorithm will be blocked. The paper proposes a new fuzzy extension of EDAS called the PFEDAS method for group decision-making. The main difference between the proposed method and the original one is that at the initial stage the individual decision matrices are not aggregated into a group matrix but are transformed into matrices of alternatives. As a result, the new PFEDAS method is based on the initial data instead of their averaged values which allows a more accurate comparison of alternatives. Using a numerical example, the PFEDAS method is compared with other similar methods known from the literature.

An integrated multi-criteria decision making approach for selecting the starting location of railroad projects

PurposeThe successful completion of linear infrastructure construction projects such as railroads, roads, tunnels, and pipelines relies heavily on decision-making processes during planning phase. Professionals in the construction industry emphasize that determining the starting point of a linear infrastructure construction project is one of the most important decisions to be made in the planning phase. However, the existing literature does not specifically focus on selection of the starting point of the segments to be constructed. Therefore, it is of utmost importance to develop a multi-criteria decision-making (MCDM) model to support selection of the starting point of the segments to be constructed in linear infrastructure construction projects.Design/methodology/approachBased on the characteristics of the railroad projects and insights gathered from expert interviews, the appropriate criteria for the model were determined. Once the criteria were determined, a decision hierarchy was developed and the weights of the criteria (w_i) were calculated using DEcision MAking Trial and Evaluation Laboratory (DEMATEL) method. Then, Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), COmplex PRoportional Assessment (COPRAS), and evaluation based on distance from average solution (EDAS) methods were used. The alternatives were ranked in terms of their priority with TOPSIS method based on relative closeness (Ci) of each alternative to the ideal solution, COPRAS method based on quantitative utility (Ui) for each alternative and EDAS method based on evaluation score (ASi) for all alternatives. The results were compared with each other.FindingsThe study reveals the effects of all criteria on the proposed model. The results of DEMATEL method indicated that quantity of aggregate (w_i = 0.075), ballast (w_i = 0.071), and sub-ballast (w_i = 0.069) are the most important criteria in starting location selection for railroads, where earthquake (w_i = 0.046), excavation cost (w_i = 0.054), and longest distance from borrow pit (w_i = 0.055) were found to be less important criteria. The starting location alternatives were ranked based on TOPSIS, COPRAS and EDAS methods. The A-1 alternative was selected as the most appropriate alternative (Ci = 0.64; Ui = 100%; ASi = 0.81), followed by A-6 alternative (Ci = 0.61; Ui = 97%; ASi = 0.73) and A-7 alternative (Ci = 0.59; Ui = 94%; ASi = 0.60). Even tough different methods were used, they provided compatible results where the same ranking was achieved except three alternatives.Originality/valueThis study identifies novel criteria for the starting location selection of railroad construction based on the data of a railroad project. This study uses different methods for selecting the starting location. Considering the project type and its scope, the model can be used by decision-makers in linear infrastructure projects for which efficient planning and effective location selection are critical for successful operations.

Processes of Self‐Management Using Evaluation Based On Distance from Average Solution (EDAS)

People with good self-management skills can effectively regulate and control their feelings, thoughts, and actions in a range of situations. Strong self-management skills allow employees to set goals on their own while making every effort to achieve them. Such employees understand how important it is to control their emotions and behavior at work. Employers like people with high self-management skills since it can be challenging for someone to control their emotions and thoughts. As a result, they might end up shouting at a client and saying harsh things to their coworkers. Self-management skills enable people to exercise more self-control, which leads to wiser professional judgements. Important jobs and activities, as well as fulfilling research goals, call for little diversion and a good capacity for concentration (4). The most crucial tasks are identified, prioritized, and concentrated on by researchers, who also try to avoid distractions. In order to efficiently handle their time, simplify daily tasks, and keep crucial information and things close at hand, researchers create organizational systems. Finally, they get ready to start the job at hand. They arrive early for classes, meetings, and presentations. After leaving for the day, they make plans for the next day. A novel and effective MCDM is designed based on the separation to the mean solution evaluations (EDAS). In this manner, alternatives are chosen depending on how much they deviate analysis, the EDAS approach (Avg evaluation adjusted for distance from solution) is the best choice. The solution with the greatest separation from the ideal is short range and negative, although the comparison between these distances is insignificant. Alternative: Overall sample n 605, 6th graders in 309, 8th graders in 296. Self-management strategies, perceived barriers, Perceived barriers, Outcome expectancy. Results: From the result it is seen that Outcome expectancy is got the first rank where as is the perceived barriers is having the lowest rank.

Evaluation of CNC lathe machine with fuzzy linguistic mcdm methods

CNC (Computerized Numerical Control) lathes have become integral to modern manufacturing and machining industries due to their ability to produce intricate parts with precision and efficiency. Not only do CNC lathes enhance productivity and accuracy, but they also minimize human error and enhance overall safety in the manufacturing process. Furthermore, the current market offers a wide array of diverse types of CNC lathes. Consequently, the evaluation and selection of CNC lathes pose a complex decision-making challenge as there are numerous types available, each with a variety of selection criteria for manufacturers to consider. It is crucial to make an informed choice, as improper evaluation and selection can have adverse effects on the overall performance of the production system. In this study, we propose using the fuzzy EDAS (Evaluation Based on Distance from Average Solution) model to evaluate and select CNC lathes. Initially, we employ the fuzzy analysis method, based on expert opinions, to establish a set of weights for the evaluation criteria. These criteria consist of seven factors: capital cost, spindle speed, distance between centers, rapid traverse rates in the X-axis and Z-axis, maximum machining diameter, and maximum machining length. Subsequently, the fuzzy EDAS object ranking model is utilized to evaluate and rank the CNC lathes, ultimately aiding in the selection of the most suitable machine for the manufacturer. The results obtained from our analysis reveal that the MICROTURN-300DX machine is the optimal choice, closely followed by the MICROTURN-300X machine. The study's findings serve as valuable guidelines for decision makers in selecting CNC lathes that align with the requirements of factory production. Moreover, the suggested approach can also be utilized to choose various other machine types as production demands become more intricate

Unveiling Afghanistan's wind and hydrogen potential: a comparative study.

Given the detrimental environmental impacts of fossil fuels, there is a gradual worldwide shift towards renewable energy sources. Wind power, renowned for its cost-effectiveness and simplicity, has been widely embraced. Despite Afghanistan facing significant challenges in its energy sector, its considerable wind energy potential offers a chance to mitigate some of these issues. This study employed a multi-criteria decision-making approach to evaluate potential wind-hydrogen project sites in Afghanistan, encompassing economic, technical, social, risk, and environmental considerations. Five criteria and sub-criteria for wind-hydrogen project implementation were analyzed using the Step-wise Weight Assessment Ratio Analysis (SWARA) method. The Weighted Aggregated Sum Product Assessment (WASPAS), Additive Ratio Assessment (ARAS), Evaluation based on Distance from Average Solution (EDAS), and Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) methods were then applied to prioritize provinces for wind-hydrogen project implementation. The analysis found that the Duration of the Payback Period and Levelized Cost of Electricity (LCOE) with weight of 6.6% and 5.6% were critical sub-criteria. Farah, Herat, and Nimroz emerged as Afghanistan's most promising provinces for wind-hydrogen energy development. In Farah, utilizing 900-kW turbines, it is feasible to generate 2679.8 MWh of electricity and produce 43.4 tons of hydrogen annually, with a Levelized Cost of Electricity of 0.0690 $/kWh and Levelized Cost of Hydrogen of 1.747 $/kg.

Flood susceptibility assessment of Jhelum River Basin: A comparative study of TOPSIS, VIKOR and EDAS methods

Floods are frequent natural hazards that cause widespread destruction, particularly in low-elevated areas. This study focuses on identifying flood susceptible zones in the Kashmir Valley, known for historical flooding attributed to the overflow of the Jhelum River. Various Multi-Criteria Decision Making (MCDM) techniques, including Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Vise Kriterijumska Optimizacijai Compromission Resenje (VIKOR), and Evaluation Based on Distance from Average Solution (EDAS), were employed in this research. A total of 17 multidimensional factors were considered, and multicollinearity tests revealed no correlation among these factors. The results of the MCDM models indicate that areas along the Jhelum River are classified under very high flood susceptible zone. Specifically, Srinagar city is consistently classified under very high flood susceptible zone by all three models. Approximately 4.27 %, 9.67 %, and 5.39 % of the total area were identified as very high susceptible areas by TOPSIS, VIKOR, and EDAS, respectively. The models exhibited robust performance, as evidenced by the Area Under the Curve of the Receiver Operating Characteristics curve (AUC-ROC). Notably, VIKOR demonstrated excellent performance among the three models in generating flood susceptible maps. The favorable outcomes of these models underscore their potential application in similar regions facing comparable challenges. This study carries significant implications for policymakers, administrators, and local authorities involved in flood management within the Kashmir Valley. The insights provided can inform proactive measures and strategies to mitigate the impact of floods and enhance the overall resilience of the region.

Exploring and evaluating the development of an open application programming interface (Open API) architecture for the fintech services ecosystem

PurposeThe Open API (application programming interface) architecture will play an important role in promoting future FinTech service applications; however, it involves user data, and the current specialization and progression are less visible. Therefore, an evaluation framework for Open API development in the FinTech service ecosystem is constructed in this study.Design/methodology/approachThis study preliminarily selects the four most important key objects and factors of this ecosystem and conducts expert interviews to revise the evaluation framework. Then, this study uses the fuzzy analytic hierarchy process (FAHP) to evaluate the objects and their factor weights and finally uses the FAHP analysis results to further apply the evaluation based on distance from average solution (EDAS) approach to explore the strategy optimization scenarios.FindingsAccording to the analysis results, the co-creation object and productivity object are the two most significant objects, with weights of 0.275 and 0.272, respectively. The analysis shows that FinTech-related companies expect to increase productivity through co-creation. Finally, the results also indicate that mobile payment is the best Open API application scenario in the FinTech service ecosystem, followed by online banking. These results illustrate strategic and management implications.Originality/valueThis study screens key evaluation criteria with a literature review and expert questionnaire interviews to process quantitative research. It can determine the weights of objectives and criteria to clarify the strength of influence between the objectives and criteria. Next, this study measures the probable performance of Open API applied in various FinTech service ecosystem scenarios.

Multi-criteria decision-making techniques for groundwater potentiality mapping in arid regions: A case study of Wadi Yiba, Kingdom of Saudi Arabia

Freshwater demand is further stressed due to the impacts of climate change and the rapid expansion of the population, particularly in dry and extremely dry regions where groundwater serves as a crucial water source. This study employed various multi-criteria decision making (MCDM) techniques to identify areas with potential for groundwater in Wadi Yiba, Kingdom of Saudi Arabia (KSA). A total of 14 parameters, including Geology, land use and land cover (LULC), Drainage Density (DD), Lineament density (LD), normalized difference vegetation index (NDVI), normalized difference water index (NDWI), rainfall, and others, were selected to create thematic layers for the delineation of groundwater potential zones (GWPZ). Using three MCDM techniques, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Vise Kriterijumska Optimizacijaik Ompromisno Resenje (VIKOR), and Evaluation Based on Distance from Average Solution (EDAS) methods, maps were generated to indicate the GWPZ in the study area. These maps were categorized into five categories: very low, low, medium, high, and very high. Results indicate that the GWPZ assessed by TOPSIS in Wadi Yiba categorizes 3% of the area as having very low groundwater potential, 9% as low, 29% as medium, 36% as high, and 23% as very high. In contrast, VIKOR classified the study region as 7%, 20%, 18%, 28%, and 26% for the five classes; while the EDAS study reveals a more balanced distribution, with 5.81%, 24.80%, 33.74%, 22.32%, and 13.33% for the five classes. We evaluated the accuracy of the final maps using the receiver operating characteristic-area under the curve (ROC-AUC) evaluation method. TOPSIS exhibited the highest accuracy (0.703), closely followed by VIKOR (0.701) and EDAS (0.557). TOPSIS and VIKOR were rated "excellent," while EDAS as "good". The findings are crucial for sustainable groundwater management in Wadi Yiba and underscore the importance of selecting appropriate methods in environmental modeling.

A novel approach employing hesitant intuitionistic fuzzy linguistic Einstein aggregation operators within the EDAS approach for multicriteria group decision making

The Evaluation based on Distance from Average Solution (EDAS) is a multi-criteria decision analysis (MCDA) technique that uses various distances from average values to make decisions. It bears resemblance to other distance-based approaches like SPOTIS, VIKOR or TOPSIS, except that instead of positive and negative ideal solutions, it uses an average solution. For hesitant intuitionistic fuzzy linguistic term sets (HIFLTSs), we first define several operational laws and aggregation operators. As a follow-up, the hesitating intuitionistic fuzzy linguistic Einstein weighted averaging (HIFLEWA) operator is introduced. In this study, the EDAS technique is used to address a multi-criteria group decision making (MCGDM) issue by utilizing the suggested operational laws and aggregation operators for HIFLTSs, aiming to mitigate the uncertainties of decision makers (DMs). A representative numerical example is employed to illustrate the strength and logical soundness of our proposed method in identifying the optimal choice under the given limitations. A comparison examination with the existing TOPSIS approach is also performed to ensure that the results generated with EDAS are accurate.

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.