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Decision Making Theories and Methods Based on Interval-Valued Intuitionistic Fuzzy Sets
by Shuping Wan Jiuying DongThis is the first book to provide a comprehensive and systematic introduction to the ranking methods for interval-valued intuitionistic fuzzy sets, multi-criteria decision-making methods with interval-valued intuitionistic fuzzy sets, and group decision-making methods with interval-valued intuitionistic fuzzy preference relations. Including numerous application examples and illustrations with tables and figures and presenting the authors’ latest research developments, it is a valuable resource for researchers and professionals in the fields of fuzzy mathematics, operations research, information science, management science and decision analysis.
Decision-making Tools to Support Innovation: Guidelines and Case Studies
by Manon Enjolras Daniel Galvez Mauricio CamargoScientific thinking concerning the way in which we drive innovation has been widely developed in recent years. It is known that the process of innovation consists of a succession of decision-making processes that require simultaneous technical, economical, organizational and sustainable compromises. Indeed, all innovative activities in business require stakeholders to seek out the best compromise between various, often contradictory dimensions of the same problems. Through studying practical cases from various fields (e.g. energy, marketing and sustainable development), this book addresses all the stages of the innovation process, highlighting some of the main decisions that can be faced by organizations. Based on the historical research conducted at the ERPI Laboratory (University of Lorraine) in Nancy, France, this book presents six innovation practices: strategy, creativity, design, project management, human resources and capitalization of knowledge. These practices are then illustrated through examples of decision support methods' applications.
Decision Making under Constraints (Studies in Systems, Decision and Control #276)
by Vladik Kreinovich Martine CeberioThis book presents extended versions of selected papers from the annual International Workshops on Constraint Programming and Decision Making from 2016 to 2018. The papers address all stages of decision-making under constraints: (1) precisely formulating the problem of multi-criteria decision-making; (2) determining when the corresponding decision problem is algorithmically solvable; (3) finding the corresponding algorithms and making these algorithms as efficient as possible; and (4) taking into account interval, probabilistic, and fuzzy uncertainty inherent in the corresponding decision-making problems. In many application areas, it is necessary to make effective decisions under constraints, and there are several area-specific techniques for such decision problems. However, because they are area-specific, it is not easy to apply these techniques in other application areas. As such, the annual International Workshops on Constraint Programming and Decision Making focus on cross-fertilization between different areas, attracting researchers and practitioners from around the globe. The book includes numerous papers describing applications, in particular, applications to engineering, such as control of unmanned aerial vehicles, and vehicle protection against improvised explosion devices.
Decision Making Under Uncertainty and Constraints: A Why-Book (Studies in Systems, Decision and Control #217)
by Martine Ceberio Vladik KreinovichThis book shows, on numerous examples, how to make decisions in realistic situations when we have both uncertainty and constraints. In most these situations, the book's emphasis is on the why-question, i.e., on a theoretical explanation for empirical formulas and techniques. Such explanations are important: they help understand why these techniques work well in some cases and not so well in others, and thus, help practitioners decide whether a technique is appropriate for a given situation. Example of applications described in the book ranges from science (biosciences, geosciences, and physics) to electrical and civil engineering, education, psychology and decision making, and religion—and, of course, include computer science, AI (in particular, eXplainable AI), and machine learning. The book can be recommended to researchers and students in these application areas. Many of the examples use general techniques that can be used in other application areas as well, so it is also useful for practitioners and researchers in other areas who are looking for possible theoretical explanations of empirical formulas and techniques.
Decision Making Under Uncertainty and Reinforcement Learning: Theory and Algorithms (Intelligent Systems Reference Library #223)
by Christos Dimitrakakis Ronald OrtnerThis book presents recent research in decision making under uncertainty, in particular reinforcement learning and learning with expert advice. The core elements of decision theory, Markov decision processes and reinforcement learning have not been previously collected in a concise volume. Our aim with this book was to provide a solid theoretical foundation with elementary proofs of the most important theorems in the field, all collected in one place, and not typically found in introductory textbooks. This book is addressed to graduate students that are interested in statistical decision making under uncertainty and the foundations of reinforcement learning.
Decision Making Under Uncertainty Via Optimization, Modelling, and Analysis (Studies in Systems, Decision and Control #558)
by Laxminarayan Sahoo Tapan Senapati Madhumangal Pal Ronald R. YagerThis book focuses on cutting-edge developments in optimal decision-making incorporating modeling and optimization for determining renewable energy sources, supply chain management, and environmental planning under uncertainty. It addresses mathematical models of cost-effective management policies. This book presents the best decision-making practices for solving real-world challenges. This book provides access to an invaluable collection of various decision-making issues that scholars and industry practitioners use as a reference. The readers are able to understand how decision-making problems are formulated under uncertainty and how to use right optimization strategies to fix problems.
Decision Making Under Uncertainty, with a Special Emphasis on Geosciences and Education (Studies in Systems, Decision and Control #218)
by Laxman Bokati Vladik KreinovichThis book describes new techniques for making decisions in situations with uncertainty and new applications of decision-making techniques. The main emphasis is on situations when it is difficult to decrease uncertainty. For example, it is very difficult to accurately predict human economic behavior, so in economics, it is very important to take this uncertainty into account when making decisions. Other areas where it is difficult to decrease uncertainty are geosciences and teaching. The book analyzes the general problem of decision making and shows how its results can be applied to economics, geosciences, and teaching. Since all these applications involve computing, the book also shows how these results can be applied to computing, including deep learning and quantum computing. The book is recommended to researchers, practitioners, and students who want to learn more about decision making under uncertainty—and who want to work on remaining challenges.
Decision Making with Spherical Fuzzy Sets: Theory and Applications (Studies in Fuzziness and Soft Computing #392)
by Cengiz Kahraman Fatma Kutlu GündoğduThis book introduces readers to the novel concept of spherical fuzzy sets, showing how these sets can be applied in practice to solve various decision-making problems. It also demonstrates that these sets provide a larger preference volume in 3D space for decision-makers. Written by authoritative researchers, the various chapters cover a large amount of theoretical and practical information, allowing readers to gain an extensive understanding of both the fundamentals and applications of spherical fuzzy sets in intelligent decision-making and mathematical programming.
Decision Making with Uncertainty in Stormwater Pollutant Processes: A Perspective on Urban Stormwater Pollution Mitigation (SpringerBriefs in Water Science and Technology)
by Buddhi Wijesiri An Liu Prasanna Egodawatta James McGree Ashantha GoonetillekeThis book presents new findings on intrinsic variability in pollutant build-up and wash-off processes by identifying the characteristics of underlying process mechanisms, based on the behaviour of various-sized particles. The correlation between build-up and wash-off processes is clearly defined using heavy metal pollutants as a case study. The outcome of this study is an approach developed to quantitatively assess process uncertainty, which makes it possible to mathematically incorporate the characteristics of variability in build-up and wash-off processes into stormwater quality models. In addition, the approach can be used to quantify process uncertainty as an integral aspect of stormwater quality predictions using common uncertainty analysis techniques. The information produced using enhanced modelling tools will promote more informed decision-making, and thereby help to improve urban stormwater quality.
Decision Modes in Complex Task Environments
by Norbert Steigenberger Thomas Lübcke Heather Fiala Alina RiebschlägerDespite intense research on decision-making in action, we still know little about when decision-makers rely on deliberate vs. intuitive decision-making in decision situations under complexity and uncertainty. Building on default-interventionist dual-processing theory, this book studies decision-making modes (deliberate vs. intuitive) in complex task environments contingent on perceived complexity, experience, and decision style preference. We find that relatively inexperienced decision-makers respond to increases in subjective complexity with an increase in deliberation and tend to follow their decision style preference. Experienced decision-makers are less guided by their decision preference and respond to increases in subjective complexity only minimally. This book contributes to a developing stream of research linking decision-making with intra-personal and environmental properties and fosters our understanding of the conditions under which decision-makers rely on intuitive vs. deliberate decision modes. In doing so, we go one step further towards a comprehensive theory of decision-making in action.
Decision Options: The Art and Science of Making Decisions (Chapman & Hall/CRC Finance Series)
by Gill EapenThrough theory and case studies, this book details how uncertainty and flexibility can be evaluated to assist in making better investment decisions in companies. It delivers an excellent balance of theory and practice in the area of investment decision making, demonstrates how financial and real options are related, and describes the theoretical underpinnings of both. The author presents case studies from diverse industries, including life sciences, pharmaceuticals, commodities, energy, technology, manufacturing, and financial services. He also looks at how organizations can become successful using a holistic framework that integrates uncertainty and flexibility.
Decision Policies for Production Networks
by Dieter Armbruster Karl G. KempfThe financial results of any manufacturing company can be dramatically impacted by the repetitive decisions required to control a complex production network be it a network of machines in a factory; a network of factories in a company; or a network of companies in a supply chain. Decision Policies for Production Networks presents recent convergent research on developing policies for operating production networks including details of practical control and decision techniques which can be applied to improve the effectiveness and economic efficiency of production networks worldwide. Researchers and practitioners come together to explore a wide variety of approaches to a range of topics including: WIP and equipment management policies, Material release policies, Machine, factory, and supply chain network policies for delivery in the face of supply and demand variability, and Conflicts between complex production network models and their controlling policies. Case studies and relevant mathematical techniques are included to support and explain techniques such as heuristics, global and hierarchical optimization, control theory and filtering approaches related to complex systems or traffic flows. Decision Policies for Production Networks acts as handbook for researchers and practitioners alike, providing findings and information which can be applied to develop methods and advance further research across production networks.
Decision Science for Future Earth: Theory and Practice
by Tetsukazu YaharaThis open access book provides a theoretical framework and case studies on decision science for regional sustainability by integrating the natural and social sciences. The cases discussed include solution-oriented transdisciplinary studies on the environment, disasters, health, governance and human cooperation. Based on these case studies and comprehensive reviews of relevant works, including lessons learned from past failures for predictable surprises and successes in adaptive co-management, the book provides the reader with new perspectives on how we can co-design collaborative projects with various conflicts of interest and how we can transform our society for a sustainable future. The book makes a valuable contribution to the global research initiative Future Earth, promoting transdisciplinary studies to bridge the gap between science and society in knowledge generation processes and supporting efforts to achieve the UN’s Sustainable Development Goals (SDGs). Compared to other publications on transdisciplinary studies, this book is unique in that evolutionary biology is used as an integrator for various areas related to human decision-making, and approaches social changes as processes of adaptive learning and evolution. Given its scope, the book is highly recommended to all readers seeking an integrated overview of human decision-making in the context of social transformation.
Decision Sciences: Theory and Practice
by Raghu Nandan Sengupta, Aparna Gupta and Joydeep DuttaThis handbook is an endeavour to cover many current, relevant, and essential topics related to decision sciences in a scientific manner. Using this handbook, graduate students, researchers, as well as practitioners from engineering, statistics, sociology, economics, etc. will find a new and refreshing paradigm shift as to how these topics can be put to use beneficially. Starting from the basics to advanced concepts, authors hope to make the readers well aware of the different theoretical and practical ideas, which are the focus of study in decision sciences nowadays. It includes an excellent bibliography/reference/journal list, information about a variety of datasets, illustrated pseudo-codes, and discussion of future trends in research. Covering topics ranging from optimization, networks and games, multi-objective optimization, inventory theory, statistical methods, artificial neural networks, times series analysis, simulation modeling, decision support system, data envelopment analysis, queueing theory, etc., this reference book is an attempt to make this area more meaningful for varied readers. Noteworthy features of this handbook are in-depth coverage of different topics, solved practical examples, unique datasets for a variety of examples in the areas of decision sciences, in-depth analysis of problems through colored charts, 3D diagrams, and discussions about software.
Decision Support for Product Development: Using Computational Intelligence for Information Acquisition in Enterprise Databases (Computational Intelligence Methods and Applications)
by Marcin RelichThis book describes how to use computational intelligence and artificial intelligence tools to improve the decision-making process in new product development. These approaches, including artificial neural networks and constraint satisfaction solutions, enable a more precise prediction of product development performance compared to widely used multiple regression models. They support decision-makers by providing more reliable information regarding, for example, project portfolio selection and project scheduling.The book is appropriate for computer scientists, management scientists, students and practitioners engaged with product innovation and computational intelligence applications.
Decision Support Methods in Modern Transportation Systems and Networks (Lecture Notes in Networks and Systems #208)
by Grzegorz Sierpiński Elżbieta MacioszekThis book contains an abundance of numerical analyses based on significant data sets, illustrating importance of environmentally friendly solutions requiring transport networks to be redesigned or clean zones to be implemented. What kind of steps should be taken to redesign transport network? How to evaluate efficiency or flexibility of transport system and city logistics? What factors can be taken into account in the process of optimizing the functioning of public transport or paid parking zones? How to optimize supply chains (including last mile delivering and routing problem)? Which of the multi-criteria methods should be applied to support decision making processes while tackling problems of global transport systems? Answers to these and many other questions can be found in this book.With regard to the research results discussed and the selected solutions applied, the book entitled "Decision support methods in modern transportation systems and networks" primarily addresses the needs of three target groups: · Scientists and researchers (ITS field)· Local authorities (responsible for the transport systems at the urban and regional level)· Representatives of business (traffic strategy management) and industry (manufacturers of ITS components).
Decision Support System: Tools and Techniques
by Susmita BandyopadhyayThis book presents different tools and techniques used for Decision Support Systems (DSS), including decision tree and table, and their modifications, multi-criteria decision analysis techniques, network tools of decision support, and various case-based reasoning methods supported by examples and case studies. Latest developments for each of the techniques have been discussed separately, and possible future research areas are duly identified as intelligent and spatial DSS. Features: Discusses all the major tools and techniques for Decision Support System supported by examples. Explains techniques considering their deterministic and stochastic aspects. Covers network tools including GERT and Q-GERT. Explains the application of both probability and fuzzy orientation in the pertinent techniques. Includes a number of relevant case studies along with a dedicated chapter on software. This book is aimed at researchers and graduate students in information systems, data analytics, operation research, including management and computer science areas.
Decision Support Systems for Weed Management
by Guillermo R. Chantre José L. González-AndújarWeed management Decision Support Systems (DSS) are increasingly important computer-based tools for modern agriculture. Nowadays, extensive agriculture has become highly dependent on external inputs and both economic costs, as well the negative environmental impact of agricultural activities, demands knowledge-based technology for the optimization and protection of non-renewable resources. In this context, weed management strategies should aim to maximize economic profit by preserving and enhancing agricultural systems. Although previous contributions focusing on weed biology and weed management provide valuable insight on many aspects of weed species ecology and practical guides for weed control, no attempts have been made to highlight the forthcoming importance of DSS in weed management. This book is a first attempt to integrate `concepts and practice’ providing a novel guide to the state-of-art of DSS and the future prospects which hopefully would be of interest to higher-level students, academics and professionals in related areas.
Decision System in Agricultural Pest Management
by Ali Rajabpour Fatemeh YarahmadiThis book covers the theoretical and practical aspects of pest population components, explaining the probable reasons for pest density fluctuations and outbreaks in agricultural or other ecosystems. Agricultural pest management is a complex task that involves dealing with a variety of pests, including insects, diseases, and weeds. Decision systems can help farmers navigate this complexity by providing structured approaches to identify, monitor, and control pests. By making informed decisions based on data and models, farmers can reduce unnecessary pesticide applications, minimizing environmental impact and saving costs. This book aids in predicting pest outbreaks using population growth parameters and estimating economic crop losses through critical thresholds, illustrated with simple case studies. Additionally, the book covers image processing, remote sensing monitoring, and other novel methods for monitoring and quickly forecasting pest population outbreaks to developintegrated pest management (IPM) programs. The book is valuable for agricultural and entomological students (graduates and postgraduates), researchers, as well as pest managers and farmers.
Decision Trees for Fault Diagnosis in Circuits and Switching Networks (Studies in Systems, Decision and Control #493)
by Monther Busbait Mikhail Moshkov Albina Moshkova Vladimir ShevtchenkoIn this book, we study decision trees for fault diagnosis in circuits and switching networks, which are among the most fundamental models for computing Boolean functions. We consider two main cases: when the scheme (circuit or switching network) has the same mode of operation for both calculation and diagnostics, and when the scheme has two modes of operation—normal for calculation and special for diagnostics. In the former case, we get mostly negative results, including superpolynomial lower bounds on the minimum depth of diagnostic decision trees depending on scheme complexity and the NP-hardness of construction diagnostic decision trees. In the latter case, we describe classes of schemes and types of faults for which decision trees can be effectively used to diagnose schemes, when they are transformed into so-called iteration-free schemes. The tools and results discussed in this book help to understand both the possibilities and challenges of using decision trees to diagnose faults in various schemes. The book is useful to specialists both in the field of theoretical and technical diagnostics.It can also be used for the creation of courses for graduate students.
Decision Trees Versus Systems of Decision Rules: A Rough Set Approach (Studies in Big Data #160)
by Kerven Durdymyradov Mikhail Moshkov Azimkhon OstonovThis book explores, within the framework of rough set theory, the complexity of decision trees and decision rule systems and the relationships between them for problems over information systems, for decision tables from closed classes, and for problems involving formal languages. Decision trees and systems of decision rules are widely used as means of representing knowledge, as classifiers that predict decisions for new objects, as well as algorithms for solving various problems of fault diagnosis, combinatorial optimization, etc. Decision trees and systems of decision rules are among the most interpretable models of knowledge representation and classification. Investigating the relationships between these two models is an important task in computer science. The possibilities of transforming decision rule systems into decision trees are being studied in detail. The results are useful for researchers using decision trees and decision rule systems in data analysis, especially in rough set theory, logical analysis of data, and test theory. This book is also used to create courses for graduate students.
Decision Trees with Hypotheses (Synthesis Lectures on Intelligent Technologies)
by Mohammad Azad Igor Chikalov Shahid Hussain Mikhail Moshkov Beata ZieloskoIn this book, the concept of a hypothesis about the values of all attributes is added to the standard decision tree model, considered, in particular, in test theory and rough set theory. This extension allows us to use the analog of equivalence queries from exact learning and explore decision trees that are based on various combinations of attributes, hypotheses, and proper hypotheses (analog of proper equivalence queries). The two main goals of this book are (i) to provide tools for the experimental and theoretical study of decision trees with hypotheses and (ii) to compare these decision trees with conventional decision trees that use only queries, each based on a single attribute. Both experimental and theoretical results show that decision trees with hypotheses can have less complexity than conventional decision trees. These results open up some prospects for using decision trees with hypotheses as a means of knowledge representation and algorithms for computing Boolean functions. The obtained theoretical results and tools for studying decision trees with hypotheses are useful for researchers using decision trees and rules in data analysis. This book can also be used as the basis for graduate courses.
Decisions and Trends in Social Systems: Innovative and Integrated Approaches of Care Services (Lecture Notes in Networks and Systems #189)
by Daniela Soitu Šárka Hošková-Mayerová Fabrizio MaturoThis book presents a systemic perspective on the broadly perceived problem of social care, meant in terms of a network engaging balanced resources and actors to assure the functionality, in an integrative approach. The approach involves individual, institutional and organizational structures, at the micro, mezzo- and macro-levels, in their interrelations, with proper contexts for understandings, interpretations and actions by stakeholders. The papers presented suggest ways of changes, involving even participant actors as changing agents, taking into account evolving behaviors and human relations, policies and inter-institutional frameworks, from many points of view. In the first part, various aspects, notably economic and emotional, of innovative and integrated approaches to long-term care are dealt with. Different aspects are considered exemplified by legal, educational, economic, environmental, cultural and those related to the perception of aging, labor market for the elderly, perceived quality of life, etc. The planning and management of social services are discussed in terms of a functional, and effective and efficient system, with the identification and analysis of actors and processes, and transformation policies. This is done at the local, regional and global levels.
Deckungsbeitragsrechnung für Ingenieure (essentials)
by Ekbert HeringDeckungsbeiträge dienen dazu, die Fixkosten eines Unternehmens bzw. der Unternehmensbereiche zu decken. Dazu müssen die fixen und die variablen Kosten bekannt sein. Der Deckungsbeitrag DB errechnet sich aus: DB = Netto-Umsatz - variable Kosten. Diese Kenngröße kann aus der Kostenrechnung leicht ermittelt werden, da Netto-Umsatz und variable Kosten in der Regel bekannt sind. Mit einer mehrstufigen Deckungsbeitragsrechnung können verschiedene Preisuntergrenzen definiert werden. Mit Deckungsbeiträgen können auch Marktpreise kalkuliert und eine Break-Even-Analyse durchgeführt werden (Bestimmung des Break-Even-Umsatzes: Umsatz, bei der gerade kein Gewinn oder Verlust auftritt oder der Break-Even-Stückzahl: Mindeststückzahl bei Gewinn = 0). Ausführliche Beispiele und Grafiken veranschaulichen die Zusammenhänge.
Declarative Models of Concurrent Cyclic Processes (Studies in Systems, Decision and Control #438)
by Grzegorz BocewiczThis monograph presents a new declarative approach dedicated to the analysis of behaviors and synthesis of structures of Systems of Cyclic Concurrent Multimodal Processes (SCCMP). These kinds of problems are some of the most difficult cyclic scheduling problems - both from the computational side and the complexity of the models used. SCCMP is understood as a set of processes (in particular, multimodal processes) that execute operations cyclically on a set of jointly used (shared) resources (processors, machines, means of transport, etc.). They model the functioning of numerous systems encountered in practical settings and which are characterized by cyclic (periodic) behavior. Typical examples are the passenger railway system, the manufacturing system, the transportation system, and etc.Considered problems, i.e., the behavior analysis problem, the structure prototyping problem, and the problem of mutual reachability of various SCCMP behaviors, are strongly NP-hard. This feature implies that computationally-efficient algorithms need to be sought. They would enable the evaluation of selected aspects of the considered system's functions, such as service costs, transport time, etc., in real-time mode.In that context, the presented monograph fills the gap in the field of SCCMP modeling. Its aim is to present declarative models of systems of cyclic multimodal processes. Such models allow the development of computationally-efficient methods of analysis of the behavior and synthesis of the structure of SCCMP. The particular issues raised in this study concern: · Modeling of SCCMP with regular/fractal structures, i.e., structures composed of repeating fragments.· Determining the conditions of mutual reachability of various SCCMP behaviors.· Modeling of SCCMP described by fuzzy variables.The monograph is addressed to researchers, practitioners, and graduate students in operations management, operations research, computer science, and industrial engineering. Declarative models of concurrent cyclic processes will serve as an essential reference for professionals working on cyclic scheduling problems in computer science, manufacturing, communication, and transportation services, as well as in many other areas.