Increasing apprehension regarding climate change, resource scarcity, and ecological deterioration has propelled the global momentum toward sustainable energy development. In this context, green energy has become an essential part of the shift away from fossil fuels and toward a future with lower carbon emissions. However, choosing the best green energy source for a certain application or specific area is a difficult task with many facets requiring consideration. Green energy solutions necessitate careful evaluation of a wide range of qualitative criteria in contrast to traditional energy sources. We put forward a hybrid fuzzy Multi-Criteria Decision-Making (MCDM) method using interval valued Pythagorean fuzzy numbers in this paper. The possibility degree method is used in the suggested approach to derive the weights of the evaluation criteria. Next, the matrix of decisions is created, and the preferred alternative is selected by entropy theory and cosine similarity theorem. Ultimately, our goal is to develop innovative, reliable techniques using these various theorems. Combining the advantages of each approach improves decision-making proceses as they increase precision and resilience and streamline the ability to handle complicated data in a variety of situations. We utilized the proposed method to evaluate green energy alternatives in Sweden to demonstrate applicability. A sensitivity analysis of the results is conducted to test how changes in input parameters affect the final ranking. Finally, a comparison analysis is provided.

Addressing the escalating global water demands requires efficient decision-making to ensure fair access and environmental preservation amid increasing demand and climate uncertainties. Desalination emerges as a pivotal solution to combat water scarcity, especially in regions grappling with persistent water shortages. In this context, effective decision-making becomes imperative for selecting sustainable desalination practices, considering diverse technological, environmental, and economic factors. Therefore, this research aims to develop an improved decision-making framework for sustainable desalination through Dombi operations joined with the disc spherical fuzzy (D-SF) arena. The D-SF environment receives an extended weighted aggregated sum product assessment (WASPAS) methodology for decision-making purposes together with the maximizing deviation method (MDM) method for weighing attributes. The new decision-making system improves reliability through weighted averaging and weighted geometric aggregation in D-SF Dombi operations to handle uncertain data more effectively. The proposed framework undergoes case-study evaluation to demonstrate its capacity for developing sustainable desalination solutions between managing technological aspects with environmental considerations and cost control. A comparative analysis showcases the reliability of the proposed D-SF WASPAS-MDM methodology. The proposed model maintains stability according to its sensitivity testing process which proves its ability to deliver dependable decisions during uncertain situations. The D-SF-driven framework maximizes the optimization of the desalination system by its ability to synthesize technological and economic with environmental considerations. Such a cooperative approach ensures that technological advancements meet both environmental criteria and economic demands, resulting in improved efficiency as well as ecologically friendly desalination operations.

United Nations formulated Sustainable Development Goals (SDG) in 2015, which are the collection of a set of objectives to provide a world to people with peace and prosperity now and in the future. 17 goals are identified as achievable targets in 2030 and they contain elimination of poverty, hunger, inequalities and improvement of health, education, environment, security and economic conditions around the world. One of SDGs is defined as clean water and sanitation and known as SDG6. Clean water and sanitation is essential for health and well-being of people and evaluation of countries considering several indicators of SDG6 simultaneously should be done. Especially in MENA countries, clean water and sanitation is a popular topic and the main aim of this study is to develop a multi-criteria evaluation model for these countries in views of SDG6 indicators. To do so, a hybrid approach based on Interval Valued Intuitionistic Fuzzy Analytic Hierarchy Process (IVIF-AHP) and Technique of Order Preference by Similarity to Ideal Solution (TOPSIS) methods is proposed. IVIF-AHP is used to determine indicator weight values and TOPSIS is used to obtain the ranking of countries. Evaluation of MENA nations is conducted to show the viability of the suggested approach. The results of the study could be useful for sustainable management of water and sanitation systems in these countries.

Space debris refers to man-made objects that are orbiting Earth but no longer serve a useful purpose. This includes items such as defunct satellites, spent rocket stages, and other debris from space missions. Space debris can range in size from tiny flecks of paint to large satellites, and they can pose a threat to operational spacecraft and satellites, as well as to human life on Earth. As more and more satellites and spacecraft are launched into space, the amount of space debris has increased, and it has become a growing concern for space agencies and governments around the world. Some measures are being taken to reduce the amount of space debris, including designing spacecraft to be more easily deorbited at the end of their useful life, and launching cleanup missions to remove some of the largest and most dangerous debris. Over time, the amount of space debris has increased significantly, and it can pose a threat to active spacecraft and satellites. In this study, we examined the space debris removal methods, and the most important criteria scientists must consider before a space debris removal mission. We determined 9 different and important criteria for space debris removal missions then we consulted three different experienced people who have played role in space studies past 20 years to subjectively rank each criterion in order of importance. As a result of these analyzes, we listed the most essential and least essential criteria for space debris removal missions, using BWM (Best Worst Method) and FUCOM in our calculations.

The increasing population and resource constraints in the world have made life in cities complex and difficult to manage. Especially the need for energy, water and other resources has become alarming, and the management and disposal of waste materials has also emerged as an important area of risk. Although waste management has been improved over time by methods such as recycling, it cannot fully solve the problems that have occurred. The need for landfill in cities, health and environmental problems have created the need for a more effective system to solve problems. It has become vital to create a sustainable life in cities that is more efficient, and which consumes less resources and improves the desired quality of life. The increase in these needs and especially developments in information technologies have created the “smart city” concept and applications that bring great innovations and facilities in many areas such as transportation, communication, health, security, energy efficiency, water use and waste management. Smart Waste Management Systems (SWMS) emerging in this context make an important contribution to the sustainability of today's cities and play an important role in carrying human life into the future. In addition, it increases the quality of life with cost optimization, energy efficiency, in-formation management, time saving, improving hygiene, and reduction in traffic, noise, bad odor and carbon emissions. This operation, defined as “smart”, also sets an example for the use of artificial intelligence. The levels of the structures, processes and performances of the existing SWMSs show their success and thus the level of providing a sustainable life. The evaluation of these currently developing systems with their components will guide all relevant actors in the improvement of existing systems. Lack of a clear criterion used in the evaluation of SWMS required this assessment to be made with the MCDM (multi-criteria decision making) methods, which makes it possible to evaluate both objective and subjective criteria. As evaluating SWMS problem needs both tangible and intangible data, using fuzzy logic is a useful tool to solve the problem. Therefore, in the application section, the Spherical fuzzy AHP (Analytic Hierarchy Process) method is used to handle determined problem. In the application section, three alternatives are evaluated under four determined criteria. Results show that the problem is handled with Spherical fuzzy AHP method by efficiently and effectively.

Campus sustainability and climate change reduction have become a significant global concern for university administrators in recent days. Several evaluation systems of universities exist, and UI GreenMetric World University is one of the most used ranking one among them. The goal is to provide an image of current conditions relating to the green campus and sustainability of universities worldwide. The ranking system uses six main criteria and 39 sub-criteria and a numeric scoring system to evaluate universities. Unfortunately, collecting a numeric datum is not always easy for decision-makers. Decision-makers need a system using human judgments. For this aim, we proposed a new fuzzy ranking system based on a multi-stage decision-making model including DEMATEL, Cognitive maps, VIKOR, and Fuzzy inference systems. The proposed model uses 18 different criteria collected from UI GreenMetric World University ranking methodology. It captures the qualitative factors of the ranking system. To show the applicability of the method, we applied the proposed method to determine the universities’ green index. The sensitivity analysis is also performed by changing decision-makers’ weights. The results demonstrate that the proposed methodology is a useful and sensitive tool to calculate the green index of the universities with fuzzy linguistic expressions.

The fourth party logistics (4PL) is an combiner that designs and implements the holistic supply chain solutions by using skills, knowledge, technology and resources of the service provider and its customer. A 4PL provider is also a technological service provider with eligible intellectual capital and the sufficient computer/software infrastructure. Defining the most appropriate 4PL service provider from the alternatives is not easy for companies, the solution can be addressed within the framework of the Multi-Criteria Decision Making (MCDM) problem, and subjective and uncertain data are required for this solution. "Fuzzy set theory" is a helpful tool for dealing with such subjectivity and uncertainty. In recent times, extensions of fuzzy sets have been evolved to address and describe the subjectivities and uncertainties more widely. Neutrosophic sets are one of the extensions of fuzzy sets, and unlike other extensions, they use the independent indeterminacy-membership function, thereby extracting important information and improving the accuracy of the decision-making process. A neutronophic MCDM method was proposed for the assessment of 4PL providers' performance. In the application part of the study, neutrosophic language scale was used by three experts to evaluate the performance of 4PL providers. Then the closeness coefficient of each alternative was computed and sequenced in descending order. We also presented a comparative analysis with neutrosphic TOPSIS method. The results determined that the proposed neutrosophic MCDM method could be used in the performance evaluation of 4PL providers and similar problems.

Digital disruption was crucial to corporate success even before COVID-19 pandemic. The need for speed digitization has grown even more pressing since the pandemic broke out, exposing firms’ digital inadequacies and jeopardizing their operational performance. If firms in all industries are to survive and prosper in the new normal, they must undergo a significant transition. Domestic manufacturers aim to embrace Industry 4.0 technology to close the labor price gap and to be cost competitive. Internet of things (IoT) is one of the key factors in adapting to the new normal. In this study, we determine the criteria for evaluating whether IoT devices are safe and ready to adapt to the new normal. We evaluated eight different criteria and determined their impacts on evaluation process with a Fermatean fuzzy CRITIC procedure. Finally, we determined the weights of criteria.

Many individuals are facing antivirus mask scarcity with the exponential spread of COVID-19. A functional antivirus mask needs to be selected and made usable for everyone. Selection mask problem contains qualitative criteria, therefore utilizing fuzzy logic for this problem is a useful approach. To optimize the efficiency of choosing antivirus masks, we propose to use one of the new types of ordinary fuzzy sets, named Spherical fuzzy sets. For this purpose, we determine 4 different alternatives and 4 criteria. Then, we gather the data under spherical information and applied the Spherical fuzzy AHP method to the problem. Then, we propose an entropy based Spherical fuzzy AHP method. We compare the results of Spherical fuzzy AHP method, and an entropy based Spherical fuzzy AHP method. Moreover, we present a sensitivity analysis to demonstrate how our model is sensitive to changes in weights of criteria. Finally, the best antivirus mask is determined for public use and we present the advantages of the proposed method in results section.

This paper presents a new Multi-criteria Decision-Making (MCDM) method with Fermatean fuzzy sets (FFSs). The proposed method uses the entropy theory to determine the weights of criteria and utilize cosine similarity measures to determine the best alternative. First, we develop a new Fermatean fuzzy entropy formula based on the Euclidean distance between Fermatean fuzzy number (FFN) and its compliment. The properties of the proposed formula and the proof of the properties are also given. Then, Fermatean fuzzy cosine similarity measures are introduced. We develop four different Fermatean fuzzy cosine similarity measures, also properties and proof of the properties are worked out systematically. Then, the algorithm of the proposed Fermatean fuzzy MCDM method, which includes Fermatean fuzzy entropy and Fermatean fuzzy cosine similarity measures, is introduced. The advantage of the proposed method is that Fermatean fuzzy entropy calculates how much valuable knowledge the current data provides in weights of criteria, and Fermatean fuzzy cosine similarity measures define the similarity between alternatives and ideal solution and negative ideal solution, in this way the method determines the best alternative smoothly. To show the applicability of the proposed method, an illustrative example is given for third party logistic (3PL) firm evaluation problem in cold chain management. In the illustrative example section, we determine six different criteria and six different 3PL alternatives. Then, alternatives are evaluated according to the proposed Fermatean fuzzy MCDM method. Moreover, the results are compared to the Euclidean measure, and sensitivity analysis is also performed. The comparison analysis results show that our model works efficiently and effectively.

Industry 4.0 is the theorization of a manufacturing model based on the “Cyber Physical System” (CPS) idea, in which advanced computer systems can communicate with computing, communication and control capabilities enhanced devices, and are often identified with a collection of enabling technologies: Internet of things (IoT), additive manufacturing, artificial intelligence, big data and analytics, etc. The use of these technologies by companies is a measure of their industry 4.0 adaptation process. In this paper, we evaluated companies’ adaptation to Industry 4.0 according to the determined criteria by using multi-attributive border approximation area comparison (MABAC) method with q-ROFNs. The criteria are determined from the most used technologies in Industry 4.0. Finally, companies are ranked according to the results of MABAC method with q-ROFNs.

ÖzBu çalışmada, belirsizlik ortamında proje süreçlerinin çizelgelenmesine olanak tanıyan bulanık etkinlik sürelerinden oluşan

The concept of Industry 4.0Industry 4.0 arose in Germany in 2011 and spread to other countries. Industry 4.0 refers to a strategic step that was introduced by the German government seeking ways to change industrial manufacturing through digitalizationDigitalization and the development of new technologies. It introduced the world with new technologies such as cybersecurityCybersecurity, big dataBig data, the cloud, simulations, augmented realityAugmented reality, additive manufacturingAdditive manufacturing, etc. The technologies also spread to other fields of business sectors such as aviation, agricultureAgriculture, health, etc. Thanks to these technologies aviation sector underwent a change named Aviation 4.0Aviation 4.0. In this chapter, we first discuss the Industry revolution, Industry 4.0Industry 4.0, and its technologies. Then, we explain Aviation 4.0 and technologies used in Aviation 4.0. Aviation 4.0 technologies are divided into three categories as follows: Ground services application in Aviation 4.0., MaintenanceMaintenance and production in Aviation 4.0, Unmanned aerial vehicles technology in Aviation 4.0Aviation 4.0. Furthermore, we give a brief discussion about Aviation 5.0. Finally, the conclusion is given.

Group decision-making on a public service problem is often biased by untrustworthy responses of the participants, which affects negatively the outcome of the procedure. To eliminate this problem, the state-of-the-art methodologies apply fuzzy sets, generally within the frames of hybrid methodologies. The objective of the recent paper is to introduce a new hybrid model based on picture fuzzy sets and linear assignment and its first real-world application on a public transport development problem. The advantage of the proposed methodology is that it simultaneously considers the indeterminacy level of respondent evaluations on decision alternatives, and applies linear assignment to avoid subjectivity in responses. With the aim of testing the reliability of the new methodology, the results are compared with the generally applied intuitionistic fuzzy Technique of Order Preference Similarity to the Ideal Solution model. The comparative results have shown that the final outcomes of the proposed method are very similar to the well-proven reference technique, thus the hybrid picture fuzzy AHP-linear assignment model has been validated.

There are great efforts on development of new technologies in different regions of the world. Thanks to the progress of science and technology, it is possible to see some news on several kind of developments every day. As a natural result of these developments, people want emerging technologies to be included in new products they will purchase. So, companies are faced with the challenge of development in their products continuously. Automotive industry can be considered among the industrial areas, which are being affected much by these emerging technologies and automotive companies need to adapt to the new technologies rapidly. As a result of this situation, suppliers of automotive manufacturers have to improve their processes. This study focuses on developing an analytic model for a decision problem of supplier evaluation in the automotive industry. Alternative suppliers are ranked by considering several factors related to digital transformation after a multi-criteria analysis. Four alternative suppliers are evaluated based on digital technologies by considering four criteria and ranked by a Spherical fuzzy extension of TOPSIS technique.

Aviation 4.0Aviation 4.0 is related to the design of cyber-physical systems which can support humans by aviation information systems and by helping them to make decisions and to complete tasks autonomously. Within aviation 4.0 context, robotics, augmented reality, radio frequency identification, and internet of things are some components of fundamental concepts and aviation 4.0 employs information technology systems and sensors. These connected systems can interact with each other using standard internet protocols and analyze data to predict failures, configure themselves, and adapt to changes. For this aim, intelligent systems are used to interact with human users in changing and dynamic physical and social environments. An intelligent system is a machine with an embedded, internet-connected computer that can gather and analyze data and communicate with other systems. This chapter presents a literature review on the intelligent systems used in aviation 4.0Aviation 4.0 through tabular and graphical analyses.

In recent years, new forms of ordinary fuzzy sets have been introduced. Developed forms of fuzzy sets aim to identify the uncertainty thoroughly and get better maximizing outcomes. Fermatean fuzzy sets are one of the newly developed forms of ordinary fuzzy sets that identifies uncertainty comprehensively. Decision-making processes use some mathematical methods and methodologies providing experts to make the correct decision. One of these methods, the MABAC method, is based on computing the distance between each alternative and the bored approximation area. However, decision-making processes also involve ambiguity and vagueness that the fuzzy sets and fuzzy decision-making strategies can easily manage while crisp methods may not. Therefore, we aimed to propose a novel method based on MABAC method with Fermantean fuzzy sets. To achieve this aim, we briefly reviewed basic theories of Fermantean fuzzy sets. Moreover, Fermantean fuzzy MABAC method was constructed, and the steps of the decision-making process were clarified. An illustrative example is given to show the applicability of the proposed method. Additionally, comparative analyses and sensitivity analysis were conducted. As a result, we demonstrate that our model can handle the decision-making process effectively and efficiently.

Bu çalışmada perakende sektöründe et ve tavuk ürünleri satışı yapan bir firmada, çalışanların elle kaldırma işlemlerini gerçekleştirdiği sipariş hazırlama iş istasyonunda ve müşterilere hizmetin sunulduğu reyon iş istasyonundaki çalışma duruşları gözlenmiştir. Bu kapsamda, çalışanların elle kaldırma işlemi için NIOSH kaldırma denklemi modeli, reyon kısmındaki çalışma duruşları için ise REBA yöntemi kullanılmıştır. Her iki iş istasyonunda yapılan analiz sonucunda, bu bölgelerdeki çalışmaların risk seviyelerinin yüksek olduğu belirlenmiş ve iyileştirmeye ihtiyaç olduğu sonucuna varılmıştır. Sipariş hazırlama alanında gerçekleştirilen analizde, kaldırmanın başladığı paletin yükseltilebilir bir transpalet ile değiştirilmesi gerektiği ancak bu işlemin tek başına yeterli olmayacağı, ayrıca taşınan kasaların ağırlıklarının 20 kg’dan 15 kg’a düşürülmesi gerektiği önerisi firmaya sunulmuştur. Reyon alanında gerçekleştirilen çalışma öncesinde REBA puanı ilk başta 9 olarak hesaplanmış, bu istasyonda gerçekleştirilen iyileştirmeler sonucunda ise REBA puanı 3’e düşürülmüştür. Nihai olarak çalışma ortamında kaldırma işlemi için işletmeye öneri getirilmiş, çalışma pozisyonu için ise çeşitli iyileştirmeler sağlanarak ergonomik riskler azaltılmıştır.

Ground Handling Services (GHSs) contain detailed services for airplanes and air passengers when they remain on the airport. In this paper, GHSs received by disabled air passengers and the service provider firms were focused. Neutrosophic MULTIMOORA, a newly developed method, has been used for evalu ation. Three Turkish GHSs firms are evaluated by eight criteria. The weights of evaluation criteria are determined by Analytic Hierarchy Process. Then algorithm of Neutrosophic MULTIMOORA method is applied to the problem and sensitivity analysis is presented. In the end, the conclusion is given. Contribution of this paper to the literature is using of the Neutrosophic MULTIMOORA Method firstly for evaluation of GHSs firms.