A study of quadratic Diophantine fuzzy sets with structural properties and their application in face mask detection during COVID-19

During the COVID-19 pandemic, identifying face masks with artificial intelligence was a crucial challenge for decision support systems. To address this challenge, we propose a quadratic Diophantine fuzzy decision-making model to rank artificial intelligence techniques for detecting masks, aiming to prevent the global spread of the disease. Our paper introduces the innovative concept of quadratic Diophantine fuzzy sets (QDFSs), which are advanced tools for modeling the uncertainty inherent in a given phenomenon. We investigate the structural properties of QDFSs and demonstrate that they generalize various fuzzy sets. In addition, we introduce essential algebraic operations, set-theoretical operations, and aggregation operators. Finally, we present a numerical case study that applies our proposed algorithms to select a unique face mask detection method and evaluate the effectiveness of our techniques. Our findings demonstrate the viability of our mask identification methodology during the COVID-19 outbreak

Symmetric and Asymmetric Data in Solution Models

This book is a Printed Edition of the Special Issue that covers research on symmetric and asymmetric data that occur in real-life problems. We invited authors to submit their theoretical or experimental research to present engineering and economic problem solution models that deal with symmetry or asymmetry of different data types. The Special Issue gained interest in the research community and received many submissions. After rigorous scientific evaluation by editors and reviewers, seventeen papers were accepted and published. The authors proposed different solution models, mainly covering uncertain data in multicriteria decision-making (MCDM) problems as complex tools to balance the symmetry between goals, risks, and constraints to cope with the complicated problems in engineering or management. Therefore, we invite researchers interested in the topics to read the papers provided in the book

Uncertain Multi-Criteria Optimization Problems

Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems

Collected Papers (on Neutrosophic Theory and Applications), Volume VI

This sixth volume of Collected Papers includes 74 papers comprising 974 pages on (theoretic and applied) neutrosophics, written between 2015-2021 by the author alone or in collaboration with the following 121 co-authors from 19 countries: Mohamed Abdel-Basset, Abdel Nasser H. Zaied, Abduallah Gamal, Amir Abdullah, Firoz Ahmad, Nadeem Ahmad, Ahmad Yusuf Adhami, Ahmed Aboelfetouh, Ahmed Mostafa Khalil, Shariful Alam, W. Alharbi, Ali Hassan, Mumtaz Ali, Amira S. Ashour, Asmaa Atef, Assia Bakali, Ayoub Bahnasse, A. A. Azzam, Willem K.M. Brauers, Bui Cong Cuong, Fausto Cavallaro, Ahmet Çevik, Robby I. Chandra, Kalaivani Chandran, Victor Chang, Chang Su Kim, Jyotir Moy Chatterjee, Victor Christianto, Chunxin Bo, Mihaela Colhon, Shyamal Dalapati, Arindam Dey, Dunqian Cao, Fahad Alsharari, Faruk Karaaslan, Aleksandra Fedajev, Daniela Gîfu, Hina Gulzar, Haitham A. El-Ghareeb, Masooma Raza Hashmi, Hewayda El-Ghawalby, Hoang Viet Long, Le Hoang Son, F. Nirmala Irudayam, Branislav Ivanov, S. Jafari, Jeong Gon Lee, Milena Jevtić, Sudan Jha, Junhui Kim, Ilanthenral Kandasamy, W.B. Vasantha Kandasamy, Darjan Karabašević, Songül Karabatak, Abdullah Kargın, M. Karthika, Ieva Meidute-Kavaliauskiene, Madad Khan, Majid Khan, Manju Khari, Kifayat Ullah, K. Kishore, Kul Hur, Santanu Kumar Patro, Prem Kumar Singh, Raghvendra Kumar, Tapan Kumar Roy, Malayalan Lathamaheswari, Luu Quoc Dat, T. Madhumathi, Tahir Mahmood, Mladjan Maksimovic, Gunasekaran Manogaran, Nivetha Martin, M. Kasi Mayan, Mai Mohamed, Mohamed Talea, Muhammad Akram, Muhammad Gulistan, Raja Muhammad Hashim, Muhammad Riaz, Muhammad Saeed, Rana Muhammad Zulqarnain, Nada A. Nabeeh, Deivanayagampillai Nagarajan, Xenia Negrea, Nguyen Xuan Thao, Jagan M. Obbineni, Angelo de Oliveira, M. Parimala, Gabrijela Popovic, Ishaani Priyadarshini, Yaser Saber, Mehmet Șahin, Said Broumi, A. A. Salama, M. Saleh, Ganeshsree Selvachandran, Dönüș Șengür, Shio Gai Quek, Songtao Shao, Dragiša Stanujkić, Surapati Pramanik, Swathi Sundari Sundaramoorthy, Mirela Teodorescu, Selçuk Topal, Muhammed Turhan, Alptekin Ulutaș, Luige Vlădăreanu, Victor Vlădăreanu, Ştefan Vlăduţescu, Dan Valeriu Voinea, Volkan Duran, Navneet Yadav, Yanhui Guo, Naveed Yaqoob, Yongquan Zhou, Young Bae Jun, Xiaohong Zhang, Xiao Long Xin, Edmundas Kazimieras Zavadskas

Airport strategic planning under uncertainty: fuzzy dual dynamic programming approach

Les aéroports sont des connecteurs critiques dans le système opérationnel de transport aérien. Afin de répondre à leurs obligations opérationnelles, économiques et sociales dans un environnement très volatil, ont besoin d'aéroports à embrasser le changement plutôt que d'y résister. Comme toute autre industrie, font face à des aéroports un large éventail de risques, dont certains spécifiques au transport aérien, les autres ayant seulement une influence indirecte mais assez puissant pour perturber les activités aéroportuaires. La planification longue terme de l'aéroport est devenue une question complexe en raison de la croissance constante de la demande de trafic aérien. Une nouvelle dimension de complexité est apparue lorsque l'incertitude a commencé à avoir un impact plus en plus perturbatrice, et significativement coûteuse sur le développement des infrastructures aéroportuaires. Historiquement, la capacité des outils traditionnels pour atténuer le risque et l'incertitude ont avérée inefficace. D'innombrables événements imprévus comme les attaques terroristes, la récession économique, les catastrophes naturelles, ont eu un impact dramatique sur les niveaux de trafic, certains avec une portée mondiale. Pour ce type hautement improbable d'événements peut être ajouté les progrès technologiques, de nouvelles modèles d'affaires des compagnies aériennes et aéroports, les changements de politique et de réglementation, préoccupation croissante pour l'impact environnemental. Dans ce contexte, la thèse met en avant une approche novatrice pour aborder l'évaluation des risques et de l'atténuation dans l'incertitude dans les projets de développement des infrastructures aéroportuaires à long terme. La thèse se développe sur le formalisme récemment développée de nombres flous comme un outil clé pour aborder l'incertitude. Après un examen approfondi de l'industrie aéroportuaire dans le contexte des environnements incertains, nombres double flous et double floue arithmétiques sont introduits. Comme le projet de développement des infrastructures aéroportuaires est un autre cas de problème de prise de décision en plusieurs étapes, la programmation dynamique est prise en compte afin d'optimiser le processus séquentiel de prise de décision. L'originalité de l'approche réside dans le fait que l'ensemble du processus sera floue et la composante double floue de la programmation dynamique sera introduite. Pour valider notre méthode, une étude de cas sera développée.Airports are critical connectors in the air transportation operational system. In order to meet their operational, economic and social obligations in a very volatile environment, airports need to embrace change rather than resist it. Like any other industry, airports face a wide array of risks, some specific to air transportation, other having only an indirect influence but powerful enough to disrupt airport activities. Long term airport planning has become a complex issue due to the constant growth in air traffic demand. A new dimension of complexity emerged when uncertainty began having a more, and more disruptive, and significantly costly impact on developing airport infrastructure. Historically, the ability of traditional risk and uncertainty mitigation tools proved inefficient. Countless unforeseen events like terrorist attacks, economic recession, natural disasters, had a dramatic impact on traffic levels, some with a global reach. To these highly improbable type of events can be added technological advancements, new airlines and airports business models, policy and regulation changes, increasing concern for environmental impact. In this context, the thesis puts forward an innovative approach for addressing risk assessment and mitigation under uncertainty in long-term airport infrastructure development projects. The thesis expands on the newly developed formalism of fuzzy dual numbers as a key tool to address uncertainty. After a comprehensive review of the airport industry in the context of uncertain environments, fuzzy dual numbers and fuzzy dual calculus are introduced. Since airport infrastructure development project is another case of multi-stage decision-making problem, dynamic programming is considered in order to optimize the sequential decision making process. The originality of the approach resides in the fact that the entire process will be fuzzified and fuzzy dual dynamic programming components will be introduced. To validate our method, a study case will be developed

Multi-Objective and Multi-Attribute Optimisation for Sustainable Development Decision Aiding

Optimization is considered as a decision-making process for getting the most out of available resources for the best attainable results. Many real-world problems are multi-objective or multi-attribute problems that naturally involve several competing objectives that need to be optimized simultaneously, while respecting some constraints or involving selection among feasible discrete alternatives. In this Reprint of the Special Issue, 19 research papers co-authored by 88 researchers from 14 different countries explore aspects of multi-objective or multi-attribute modeling and optimization in crisp or uncertain environments by suggesting multiple-attribute decision-making (MADM) and multi-objective decision-making (MODM) approaches. The papers elaborate upon the approaches of state-of-the-art case studies in selected areas of applications related to sustainable development decision aiding in engineering and management, including construction, transportation, infrastructure development, production, and organization management

Z-Numbers-Based Approach to Hotel Service Quality Assessment

In this study, we are analyzing the possibility of using Z-numbers for measuring the service quality and decision-making for quality improvement in the hotel industry. Techniques used for these purposes are based on consumer evalu- ations - expectations and perceptions. As a rule, these evaluations are expressed in crisp numbers (Likert scale) or fuzzy estimates. However, descriptions of the respondent opinions based on crisp or fuzzy numbers formalism not in all cases are relevant. The existing methods do not take into account the degree of con- fidence of respondents in their assessments. A fuzzy approach better describes the uncertainties associated with human perceptions and expectations. Linguis- tic values are more acceptable than crisp numbers. To consider the subjective natures of both service quality estimates and confidence degree in them, the two- component Z-numbers Z = (A, B) were used. Z-numbers express more adequately the opinion of consumers. The proposed and computationally efficient approach (Z-SERVQUAL, Z-IPA) allows to determine the quality of services and iden- tify the factors that required improvement and the areas for further development. The suggested method was applied to evaluate the service quality in small and medium-sized hotels in Turkey and Azerbaijan, illustrated by the example

Sustainable Construction Engineering and Management

This Book is a Printed Edition of the Special Issue which covers sustainability as an emerging requirement in the fields of construction management, project management and engineering. We invited authors to submit their theoretical or experimental research articles that address the challenges and opportunities for sustainable construction in all its facets, including technical topics and specific operational or procedural solutions, as well as strategic approaches aimed at the project, company or industry level. Central to developments are smart technologies and sophisticated decision-making mechanisms that augment sustainable outcomes. The Special Issue was received with great interest by the research community and attracted a high number of submissions. The selection process sought to balance the inclusion of a broad representative spread of topics against research quality, with editors and reviewers settling on thirty-three articles for publication. The Editors invite all participating researchers and those interested in sustainable construction engineering and management to read the summary of the Special Issue and of course to access the full-text articles provided in the Book for deeper analyses

Sustainable Urban Development - a Nexus of Understanding, Methodology, and Governance

Sustainability management requires facing tradeoffs between socioeconomic and environmental objectives, while integrating contextual variations into strategic and business goals to create a win-win situation. However, sustainability literature has shown a lack of consensus on the conceptualization, measurement, and operationalization of sustainability. Context-driven objectives demand multidimensional and multilateral synergies and tradeoffs that do not possess a simple generic pathway to achieve sustainable urban development. This dissertation explores the role of conceptual and methodological approaches in determining sustainability objectives, evaluating the policy development process and its implications, and identifying opportunities and constraints for local governance to localize sustainability. The study identified constraints to localizing Sustainable Development Goals and affordable housing that include distribution of authority, functional and geographic mapping, and assigning roles and responsibilities. These factors set a foundation for the subsidiarity principle, which guarantees delegation of commitment to a lower level of governance provided the federal government's role in ensuring systematic implementation of regulations and provision of necessary resources. Furthermore, the interconnectedness of SDGs requires synergies and tradeoffs to overcome potential hindrances and supplement multilateral efforts. Similarly, the complexity of the housing system demands a multidimensional approach, multisectoral integration, and a tradeoff between socioeconomic and environmental objectives. Such complexity wouldn’t be easy to address without innovative and out-of-the-box solutions to address socioeconomic and geographic differences between cities. In a complex urban environment, policies developed without considering functional and normative objectives, intergovernmental relationships, and local capacity may lead to unaccounted outcomes. Findings from this research highlight that the housing policies developed and implemented without an integrated approach may fail to achieve their intended objectives. The study confirms that speculation taxes are not an effective tool in curbing house prices. Similarly, considering the role of property taxes in providing public services, delinking property taxes from a potential contributor to house prices would provide a better lens to develop local housing policies. Furthermore, the study also confirms that the housing market can be better assessed at a local scale, considering geographical influence in conjunction with investment trends. The research advances the knowledge and theory in housing system analysis, sustainable housing, and policy-related decision-making. It paves the way for a theoretical extension of the subsidiarity theory, facilitating local government to adopt the Sustainable Development Goals framework. The evaluation further helps to generalize the conceptual approach for the subsidiarity principle in governing sustainability at a local level