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

Smart Energy and Intelligent Transportation Systems

With the Internet of Things and various information and communication technologies, a city can manage its assets in a smarter way, constituting the urban development vision of a smart city. This facilitates a more efficient use of physical infrastructure and encourages citizen participation. Smart energy and smart mobility are among the key aspects of the smart city, in which the electric vehicle (EV) is believed to take a key role. EVs are powered by various energy sources or the electricity grid. With proper scheduling, a large fleet of EVs can be charged from charging stations and parking infrastructures. Although the battery capacity of a single EV is small, an aggregation of EVs can perform as a significant power source or load, constituting a vehicle-to-grid (V2G) system. Besides acquiring energy from the grid, in V2G, EVs can also support the grid by providing various demand response and auxiliary services. Thanks to this, we can reduce our reliance on fossil fuels and utilize the renewable energy more effectively. This Special Issue “Smart Energy and Intelligent Transportation Systems” addresses existing knowledge gaps and advances smart energy and mobility. It consists of five peer-reviewed papers that cover a range of subjects and applications related to smart energy and transportation

Methodology for the evaluation and design of projects considering multiple criteria and uncertainty. Application to the development of energy projects in rural areas

Tesi en modalitat de compendi de publicacionsIn 2015, the United Nations defined the Sustainable Development Goals in a transition towards a world without poverty and where human rights, equity and sustainability are prioritized. In particular, modern energy services are considered crucial not only to achieve universal access to energy by 2030, but due to their contribution to alleviate chronical poverty, reduce food insecurity, promote the access to modern information in schools and enhance the start of productive activities. However, the aim of global access by 2030 is still far from being complete, with more than 700 million people living in rural areas without access to electricity and using firewood and other polluting traditional biomass for cooking and heating. Decentralized energy systems are gaining attention as a more feasible solution than grid extension to provide energy to rural and inaccessible areas. The evaluation and design of decentralized systems is a complex process that needs to take into account multiple alternatives and criteria to ensure a long-term sustainability, but usually available studies in literature focus exclusively in technical and economic aspects. Also, the minority of studies following a multicriteria decision-making approach underestimate the effect of the potential lack of confidence of the experts and users consulted to weight the importance of each criterion or to evaluate a specific alternative. In this context, the objective of this thesis is to develop multicriteria procedures considering uncertainty to increase the robustness of the results. These procedures are applied to projects that foster access to energy services and promote therefore the development of rural and underprivileged areas. The thesis begins with two multicriteria procedures presented for the evaluation and the design, respectively, of rural electrification projects. These procedures are applied to two real case studies in Peru and Nigeria. Both applications provide valuable insights, for local authorities and other promoters of electrification systems in similar contexts, regarding which technologies and configurations to use in determined circumstances. At the same time, the analysis carried out enable an improvement regarding the robustness of results through the consideration of the lack of confidence of the opinions collected about the importance of the criteria and the evaluation of the alternatives. In this regard, A Methodology for Multicriteria Decision-making considering Uncertainty (MIMDU) is then developed based on fuzzy numbers to include the lack of confidence experts and users might have when weighting a criterion or evaluating an alternative. The methodology designed includes a novel procedure to quantify human opinions with non-pre-defined fuzzy numbers and a systematic process to calculate diverse rankings of alternatives and provide complimentary information that leads to a more robust decision-making. Indeed, the potential of the methodology is illustrated with an example case that shows how the lack of confidence can affect the alternatives ranking and the subsequent decision. Finally, the methodology is applied to a real case study in Colombia to select the best alternative for digestate post-treatment before its application to agricultural soil as a fertilizer. The use of MIMDU presents three major beneficial outcomes for multicriteria decision-making to foster rural development. First, the consideration of the lack of confidence of the respondents can reduce the pressure they might feel when providing an answer without complete knowledge. Second, it allows a more accurate quantification of the opinions given, turning, for example, more hesitant answers into less reliable evaluations of an alternative, that worsens its final ranking. And third, more robust decisions can be taken due to the major precision in the modelling of opinions and the possibility of comparing crisp and fuzzy-based rankings of the alternatives.Dins dels objectius de desenvolupament sostenibles, els serveis energètics moderns es consideren crucials no només per aconseguir l'accés universal a l'energia el 2030, sinó per la seva contribució a pal·liar la pobresa crònica, reduir la inseguretat alimentària, promoure l'accés a la informació moderna a les escoles i permetre l'inici d'activitats productives. Tot i això, l’objectiu d’accés mundial per al 2030 encara està lluny d’acomplir-se, ja que més de 700 milions de persones viuen a les zones rurals sense accés a l’electricitat i utilitzen llenya i altres biomasses tradicionals contaminants per cuinar i escalfar. Els sistemes energètics descentralitzats guanyen pes respecte l’extensió de la xarxa per proporcionar energia a zones rurals i inaccessibles. L’avaluació i el disseny d’aquests sistemes és un procés complex que ha de tenir en compte múltiples alternatives i criteris per garantir una sostenibilitat a llarg termini, però els estudis de literatura disponibles generalment se centren exclusivament en aspectes tècniques i econòmiques. A més, la minoria d’estudis que segueixen un enfocament multicriteri subestimen l’efecte de la manca de confiança potencial dels experts i usuaris consultats per ponderar la importància de cada criteri o avaluar una alternativa específica. En aquest context, l'objectiu d'aquesta tesi és desenvolupar procediments multicriteri considerant la incertesa per afavorir l’obtenció de resultats robustos. Aquests procediments s’apliquen a projectes que afavoreixen l’accés als serveis energètics i promouen, per tant, el desenvolupament de zones rurals i desfavorides. La tesi comença amb dos procediments multicriteri presentats per a l'avaluació i el disseny, respectivament, de projectes d'electrificació rural. Aquests procediments s'apliquen a dos casos pràctics reals al Perú i Nigèria. Ambdues aplicacions proporcionen informació valuosa, per a les autoritats locals i altres promotors de sistemes d’electrificació en contextos similars, sobre quines tecnologies i configuracions a utilitzar en determinades circumstàncies. Al mateix temps, les anàlisis realitzades permeten una millora en quant a la solidesa dels resultats mitjançant la consideració de la manca de confiança de les opinions recollides sobre la importància dels criteris i l’avaluació de les alternatives. Per fer-ho, es desenvolupa una metodologia per a la presa de decisions multicriteri que té en compte la incertesa (MIMDU) basada en nombres difusos per incloure la manca de confiança que els experts i usuaris podrien tenir quan ponderen un criteri o avaluen una alternativa. La metodologia dissenyada inclou un nou procediment per quantificar opinions humanes amb nombres difusos no predefinits i un procés sistemàtic per calcular diversos rànquings d’alternatives i proporcionar informació complementària que condueix a una presa de decisions més robusta. De fet, el potencial de la metodologia s’il·lustra amb un cas d’exemple que mostra com la manca de confiança pot afectar el rànquing d’alternatives i la decisió posterior. Finalment, la metodologia s'aplica a un estudi de cas real a Colòmbia per seleccionar la millor alternativa per al post-tractament del digestat abans de la seva aplicació a sòl agrícola com a fertilitzant. L’ús de MIMDU presenta tres grans beneficis per a la presa de decisions multicriteri per fomentar el desenvolupament rural. En primer lloc, la consideració de la manca de confiança dels enquestats pot reduir la pressió que podrien sentir al donar una resposta sense coneixement complet. En segon lloc, permet una quantificació més precisa de les opinions donades, convertint, per exemple, respostes més dubtoses en avaluacions menys fiables d’una alternativa, que empitjora la seva classificació final. I, en tercer lloc, es poden prendre decisions més robustes a causa de la precisió en la modelització d’opinionsEn 2015, la Organización de las Naciones Unidas definió los Objetivos de Desarrollo Sostenible en una transición hacia un mundo sin pobreza y donde se priorizan los derechos humanos, la equidad y la sostenibilidad. En particular, los servicios energéticos modernos se consideran cruciales no solo para lograr el acceso universal a la energía en 2030, sino por su contribución para aliviar la pobreza crónica, reducir la inseguridad alimentaria, promover el acceso a la información en las escuelas y permitir el inicio de actividades productivas. Sin embargo, el objetivo de acceso global a la energía para 2030 aún está lejos de ser completo, con más de 700 millones de personas viviendo en áreas rurales sin acceso a electricidad y utilizando leña y otra biomasa tradicional contaminante, para cocinar y calentar. Los sistemas de energía descentralizados están ganando peso respecto a la extensión de la red para proporcionar energía a áreas rurales e inaccesibles. La evaluación y el diseño de sistemas descentralizados es un proceso complejo que precisa considerar múltiples alternativas y criterios para que sea sostenible a largo plazo, pero los estudios disponibles en la literatura generalmente se enfocan exclusivamente en aspectos técnicos y económicos. Asimismo, la minoría de estudios que siguen un enfoque de toma de decisiones multicriterio subestiman el efecto de la potencial falta de confianza de los expertos y usuarios consultados para ponderar la importancia de cada criterio o para evaluar una alternativa específica. En este contexto, el objetivo de esta tesis es desarrollar procedimientos multicriterio considerando la incertidumbre para aumentar la robustez de los resultados. Estos procedimientos se aplican a proyectos que fomentan el acceso a los servicios energéticos y, por tanto, promueven el desarrollo de zonas rurales y desfavorecidas. La tesis comienza con dos procedimientos multicriterio presentados para la evaluación y el diseño, respectivamente, de proyectos de electrificación rural. Estos procedimientos se aplican a dos estudios de casos reales en Perú y Nigeria. Ambas aplicaciones pueden proporcionar información valiosa, para las autoridades locales y otros promotores de sistemas de electrificación en contextos similares, sobre qué tecnologías y configuraciones utilizar en determinadas circunstancias. Al mismo tiempo, los análisis realizados permiten una mejora en cuanto a la robustez de los resultados a través de la consideración de la falta de confianza de las opiniones recogidas acerca de la importancia de los criterios y de la evaluación de las alternativas. Para ello, se desarrolla una Metodología para la toma de decisiones multicriterio considerando la incertidumbre (MIMDU) basada en números difusos para incluir la falta de confianza que los expertos y los usuarios pueden tener al ponderar un criterio o evaluar una alternativa La metodología diseñada incluye un procedimiento novedoso para cuantificar opiniones humanas con números difusos no predefinidos y un proceso sistemático para proponer rankings de alternativas y brindar información complementaria que conduce a una toma de decisiones más robusta. El potencial de la metodología se ilustra con un caso de ejemplo que muestra cómo la falta de confianza puede afectar el ranking de alternativas y la decisión posterior. Finalmente, la metodología diseñada se aplica a un estudio de caso real en Colombia para seleccionar la mejor alternativa para el digestato post-tratamiento previo a su aplicación al suelo agrícola como fertilizante. El uso de MIMDU presenta tres importantes beneficios para la toma de decisiones multicriterio en contextos de desarrollo rural. En primer lugar, la consideración de la falta de confianza de los encuestados puede reducir la presión al dar una respuesta sin un conocimiento completo. En segundo lugar, permite una cuantificación más precisa de las opiniones emitidas, convirtiendo, por ejemplo, respuestas más vacilantes en valoraciones menos fiables de una alternativa, que empeora su clasificación final. Y tercero, se pueden tomar decisiones más sólidas debido a la mayor precisión en el modelado de opiniones y la posibilidad de comparar rankings deterministas y difusos de las alternativas.Postprint (published version

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

EXPLAINABLE FEATURE- AND DECISION-LEVEL FUSION

Information fusion is the process of aggregating knowledge from multiple data sources to produce more consistent, accurate, and useful information than any one individual source can provide. In general, there are three primary sources of data/information: humans, algorithms, and sensors. Typically, objective data---e.g., measurements---arise from sensors. Using these data sources, applications such as computer vision and remote sensing have long been applying fusion at different levels (signal, feature, decision, etc.). Furthermore, the daily advancement in engineering technologies like smart cars, which operate in complex and dynamic environments using multiple sensors, are raising both the demand for and complexity of fusion. There is a great need to discover new theories to combine and analyze heterogeneous data arising from one or more sources. The work collected in this dissertation addresses the problem of feature- and decision-level fusion. Specifically, this work focuses on fuzzy choquet integral (ChI)-based data fusion methods. Most mathematical approaches for data fusion have focused on combining inputs relative to the assumption of independence between them. However, often there are rich interactions (e.g., correlations) between inputs that should be exploited. The ChI is a powerful aggregation tool that is capable modeling these interactions. Consider the fusion of m sources, where there are 2m unique subsets (interactions); the ChI is capable of learning the worth of each of these possible source subsets. However, the complexity of fuzzy integral-based methods grows quickly, as the number of trainable parameters for the fusion of m sources scales as 2m. Hence, we require a large amount of training data to avoid the problem of over-fitting. This work addresses the over-fitting problem of ChI-based data fusion with novel regularization strategies. These regularization strategies alleviate the issue of over-fitting while training with limited data and also enable the user to consciously push the learned methods to take a predefined, or perhaps known, structure. Also, the existing methods for training the ChI for decision- and feature-level data fusion involve quadratic programming (QP). The QP-based learning approach for learning ChI-based data fusion solutions has a high space complexity. This has limited the practical application of ChI-based data fusion methods to six or fewer input sources. To address the space complexity issue, this work introduces an online training algorithm for learning ChI. The online method is an iterative gradient descent approach that processes one observation at a time, enabling the applicability of ChI-based data fusion on higher dimensional data sets. In many real-world data fusion applications, it is imperative to have an explanation or interpretation. This may include providing information on what was learned, what is the worth of individual sources, why a decision was reached, what evidence process(es) were used, and what confidence does the system have on its decision. However, most existing machine learning solutions for data fusion are black boxes, e.g., deep learning. In this work, we designed methods and metrics that help with answering these questions of interpretation, and we also developed visualization methods that help users better understand the machine learning solution and its behavior for different instances of data

Algebraic Structures of Neutrosophic Triplets, Neutrosophic Duplets, or Neutrosophic Multisets

Neutrosophy (1995) is a new branch of philosophy that studies triads of the form (, , ), where is an entity {i.e. element, concept, idea, theory, logical proposition, etc.}, is the opposite of , while is the neutral (or indeterminate) between them, i.e., neither nor .Based on neutrosophy, the neutrosophic triplets were founded, which have a similar form (x, neut(x), anti(x)), that satisfy several axioms, for each element x in a given set.This collective book presents original research papers by many neutrosophic researchers from around the world, that report on the state-of-the-art and recent advancements of neutrosophic triplets, neutrosophic duplets, neutrosophic multisets and their algebraic structures – that have been defined recently in 2016 but have gained interest from world researchers. Connections between classical algebraic structures and neutrosophic triplet / duplet / multiset structures are also studied. And numerous neutrosophic applications in various fields, such as: multi-criteria decision making, image segmentation, medical diagnosis, fault diagnosis, clustering data, neutrosophic probability, human resource management, strategic planning, forecasting model, multi-granulation, supplier selection problems, typhoon disaster evaluation, skin lesson detection, mining algorithm for big data analysis, etc

Advances in Computational Intelligence Applications in the Mining Industry

This book captures advancements in the applications of computational intelligence (artificial intelligence, machine learning, etc.) to problems in the mineral and mining industries. The papers present the state of the art in four broad categories: mine operations, mine planning, mine safety, and advances in the sciences, primarily in image processing applications. Authors in the book include both researchers and industry practitioners

Numerical and Evolutionary Optimization 2020

This book was established after the 8th International Workshop on Numerical and Evolutionary Optimization (NEO), representing a collection of papers on the intersection of the two research areas covered at this workshop: numerical optimization and evolutionary search techniques. While focusing on the design of fast and reliable methods lying across these two paradigms, the resulting techniques are strongly applicable to a broad class of real-world problems, such as pattern recognition, routing, energy, lines of production, prediction, and modeling, among others. This volume is intended to serve as a useful reference for mathematicians, engineers, and computer scientists to explore current issues and solutions emerging from these mathematical and computational methods and their applications

Green Technologies for Production Processes

This book focuses on original research works about Green Technologies for Production Processes, including discrete production processes and process production processes, from various aspects that tackle product, process, and system issues in production. The aim is to report the state-of-the-art on relevant research topics and highlight the barriers, challenges, and opportunities we are facing. This book includes 22 research papers and involves energy-saving and waste reduction in production processes, design and manufacturing of green products, low carbon manufacturing and remanufacturing, management and policy for sustainable production, technologies of mitigating CO2 emissions, and other green technologies