Fuzzy Sets, Fuzzy Logic and Their Applications

The present book contains 20 articles collected from amongst the 53 total submitted manuscripts for the Special Issue “Fuzzy Sets, Fuzzy Loigic and Their Applications” of the MDPI journal Mathematics. The articles, which appear in the book in the series in which they were accepted, published in Volumes 7 (2019) and 8 (2020) of the journal, cover a wide range of topics connected to the theory and applications of fuzzy systems and their extensions and generalizations. This range includes, among others, management of the uncertainty in a fuzzy environment; fuzzy assessment methods of human-machine performance; fuzzy graphs; fuzzy topological and convergence spaces; bipolar fuzzy relations; type-2 fuzzy; and intuitionistic, interval-valued, complex, picture, and Pythagorean fuzzy sets, soft sets and algebras, etc. The applications presented are oriented to finance, fuzzy analytic hierarchy, green supply chain industries, smart health practice, and hotel selection. This wide range of topics makes the book interesting for all those working in the wider area of Fuzzy sets and systems and of fuzzy logic and for those who have the proper mathematical background who wish to become familiar with recent advances in fuzzy mathematics, which has entered to almost all sectors of human life and activity

Fuzzy Sets, Fuzzy Logic and Their Applications 2020

The present book contains the 24 total articles accepted and published in the Special Issue “Fuzzy Sets, Fuzzy Logic and Their Applications, 2020” of the MDPI Mathematics journal, which covers a wide range of topics connected to the theory and applications of fuzzy sets and systems of fuzzy logic and their extensions/generalizations. These topics include, among others, elements from fuzzy graphs; fuzzy numbers; fuzzy equations; fuzzy linear spaces; intuitionistic fuzzy sets; soft sets; type-2 fuzzy sets, bipolar fuzzy sets, plithogenic sets, fuzzy decision making, fuzzy governance, fuzzy models in mathematics of finance, a philosophical treatise on the connection of the scientific reasoning with fuzzy logic, etc. It is hoped that the book will be interesting and useful for those working in the area of fuzzy sets, fuzzy systems and fuzzy logic, as well as for those with the proper mathematical background and willing to become familiar with recent advances in fuzzy mathematics, which has become prevalent in almost all sectors of the human life and activity

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

A multicriteria methodology for estimating consumer acceptance of alternative powertrain technologies

A multicriteria methodology for estimating consumer acceptance of vehicles with alternative powertrain technologies is presented. The approach is based on the non-compensatory ELECTRE TRI method and compares hybrid, plug-in hybrid, and electric vehicles to conventional models. Criteria considered are ownership costs and restrictions to vehicle use, which apply mainly to electric vehicles. The methodology is applied to a case study of 94 vehicles of different market segments and alternative powertrains. The analysis is carried out per segment and considers two driver profiles, city and all-purpose, and a baseline scenario for all cases. Output is tested for statistical significance, with powertrain technology as disaggregating factor, and a sensitivity analysis on the base scenario is also carried out, as well as a comparison with results derived by a compensatory multicriteria method (TOPSIS). Results show that conventional vehicles are the top choice for the small vehicles segment, due to lower purchase prices and higher use flexibility. For medium sized vehicles, all powertrain technologies are competitive for city drivers, whereas for all-purpose drivers, use restrictions for electric vehicles make these less attractive. The baseline scenario and sensitivity analysis highlight that opting for an electric vehicle depends strongly on the driver's use flexibility needs. As such, an electric vehicle can be either very attractive or outright unusable, regardless of financial considerations. It is also seen that plug-in hybrids do not present any significant advantage, as compared to other, non-electric choices, due to their higher purchase prices.info:eu-repo/semantics/publishedVersion"Transport Policy" - Ano 2020, vol. 85, p. 18-3

A DECISION-SUPPORT TOOL FOR DEMOLITION SALE OF A VESSEL

The fundamental goal of any business is to create value for its owners. In shipping, the value is not only created with freight income, but also with the trade of the vessel itself. A ship has a limited lifetime and can be traded in different markets. The lowest value it will ever receive is its scrap price. An owner may decide to sell a vessel to scrap due to various reasons together with her physical condition and age. In this paper, a fuzzy Analytic Hierarchy Process based decision model is used to provide practitioners with a decision support tool for demolition sale versus further trading of a vessel. The usage of the tool is further illustrated with five actual cases

Fuzzy Sets in Business Management, Finance, and Economics

This book collects fifteen papers published in s Special Issue of Mathematics titled “Fuzzy Sets in Business Management, Finance, and Economics”, which was published in 2021. These paper cover a wide range of different tools from Fuzzy Set Theory and applications in many areas of Business Management and other connected fields. Specifically, this book contains applications of such instruments as, among others, Fuzzy Set Qualitative Comparative Analysis, Neuro-Fuzzy Methods, the Forgotten Effects Algorithm, Expertons Theory, Fuzzy Markov Chains, Fuzzy Arithmetic, Decision Making with OWA Operators and Pythagorean Aggregation Operators, Fuzzy Pattern Recognition, and Intuitionistic Fuzzy Sets. The papers in this book tackle a wide variety of problems in areas such as strategic management, sustainable decisions by firms and public organisms, tourism management, accounting and auditing, macroeconomic modelling, the evaluation of public organizations and universities, and actuarial modelling. We hope that this book will be useful not only for business managers, public decision-makers, and researchers in the specific fields of business management, finance, and economics but also in the broader areas of soft mathematics in social sciences. Practitioners will find methods and ideas that could be fruitful in current management issues. Scholars will find novel developments that may inspire further applications in the social sciences

Dynamics under Uncertainty: Modeling Simulation and Complexity

The dynamics of systems have proven to be very powerful tools in understanding the behavior of different natural phenomena throughout the last two centuries. However, the attributes of natural systems are observed to deviate from their classical states due to the effect of different types of uncertainties. Actually, randomness and impreciseness are the two major sources of uncertainties in natural systems. Randomness is modeled by different stochastic processes and impreciseness could be modeled by fuzzy sets, rough sets, Dempster–Shafer theory, etc

Study on Early Warning of Enterprise Financial Distress — Based on Partial Least-squares Logistic Regression

Establishment of an effective early warning system can make the company operators make relevant decisions as soon as possible when finding the crisis, improve the operating results and financial condition of enterprise, and can also make investors avoid or reduce investment losses. This paper applies the partial least-squares logistic regression model for the analysis on early warning of enterprise financial distress in consideration of quite sensitive characteristics of common logistic model for the multicollinearity. The data of real estate industry listed companies in China are used to compare and analyze the early warning of financial distress by using the logistic model and the partial least-squares logistic model, respectively. The study results show that compared with the common logistic regression model, the applicability of partial least-squares logistic model is stronger due to its eliminating multicollinearity problem among various early warning indicators