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Decision-Making in High Risk Organizations Under Stress Conditions
by Anthony J. Spurgin David W. StupplesThis book discusses management decision-making under accident conditions as a vehicle to confirm the importance of clear decision-making guided by a systems approach on how an organization functions related to the role of managers, operators, and the operation of the plant. The book shows how to effectively assess the reliability of an organization particularly those organizations responsible for critical infrastructure. The authors have used Stafford Beer’s cybernetic model as a basis to model the behavior and reliability of such organizations. A series of case studies are used to draw conclusions not only how training, experience, and education can improve the strategy and response of management to reduce the probability of an economic or social disaster, but also draw attention to the fact that managers need to be made aware of the consequences of their decisions. Poor management decisions made under stress conditions can lead to the collapse of an organization together with its underlying business, possibly linked to a social disaster with loss of life. Some technology-ignorant management decisions even under non-stress conditions can lead to dangerous situations, which can increase the economic burden placed on an organization. This book describes such situations in order to promote improvement in organizational preparedness by training, experience, and education to reduce safety and economic risks. This book offers:• Case studies of accidents that have affected different HROs (high-risk organizations) and others, due to poor decision-making by management• Training methods (advocated by Admiral Hyman Rickover, adopted by military bodies and others) to prepare staff to make critical decisions under difficult conditions and examine their applicability to training managers of high-risk facilities• Documentation on how making decisions in difficult situations have psychological constraints related to the degree of preparedness and the tools available to aid the decision maker(s)• Studies on the key actions taken before, during, and after accidents and how these management decisions can affect accident propagation, and how one could improve management decision-making by the use of training in decision-making and an understanding of Ross Ashby’s Law of Requisite Variety.• Simulation techniques to improve training of front-line operators and management• Consideration of cost and investment evaluations and how they can distort the selection of tactics and measures that ensure successful operations and avoidance of accidents
Decision Making in Inventory Management (Inventory Optimization)
by Nita H. Shah Mandeep Mittal Leopoldo Eduardo Cárdenas-BarrónThis book provides several inventory models for making the right decision in inventory management under different environments. Basically, the optimal ordering policies are determined for situations with and without shortages in production-inventory systems. The chapters in the book include various features of inventory modeling i.e., inflation, deterioration, supply chain, learning, credit financing, carbon emission policy, stock-dependent demand, among others. The book is a useful resource for academicians, researchers, students, practitioners, and managers who can be benefited with the policies provided in the chapters of the book.
Decision Making in Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods
by R. Venkata RaoDecision Making in Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods presents the concepts and details of applications of MADM methods. A range of methods are covered including Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), VIšekriterijumsko KOmpromisno Rangiranje (VIKOR), Data Envelopment Analysis (DEA), Preference Ranking METHod for Enrichment Evaluations (PROMETHEE), ELimination Et Choix Traduisant la Realité (ELECTRE), COmplex PRoportional ASsessment (COPRAS), Grey Relational Analysis (GRA), UTility Additive (UTA), and Ordered Weighted Averaging (OWA). The existing MADM methods are improved upon and three novel multiple attribute decision making methods for solving the decision making problems of the manufacturing environment are proposed. The concept of integrated weights is introduced in the proposed subjective and objective integrated weights (SOIW) method and the weighted Euclidean distance based approach (WEDBA) to consider both the decision maker's subjective preferences as well as the distribution of the attributes data of the decision matrix. These methods, which use fuzzy logic to convert the qualitative attributes into the quantitative attributes, are supported by various real-world application examples. Also, computer codes for AHP, TOPSIS, DEA, PROMETHEE, ELECTRE, COPRAS, and SOIW methods are included. This comprehensive coverage makes Decision Making in Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods a key reference for the designers, manufacturing engineers, practitioners, managers, institutes involved in both design and manufacturing related projects. It is also an ideal study resource for applied research workers, academicians, and students in mechanical and industrial engineering.
Decision Making in Risk Management: Quantifying Intangible Risk Factors in Projects (Manufacturing and Production Engineering)
by Christopher O. CoxProject risk management is regarded as a necessary dimension of effective project delivery. Current practices tend to focus on tangible issues such as late delivery of equipment or the implications of technology. This book introduces a framework to identify emergent behavior-centric intangible risks and the conditions that initiate them. Decision Making in Risk Management: Quantifying Intangible Risk Factors in Projects identifies the quantitative measures to assess behavior-induced risks by presenting a framework that limits the interpersonal tension of addressing behavioral risks. Included in the book is an illustrative case study from the oil and gas sector that demonstrates the use of the framework. The missing dimension of behavior-centric intangible risk factors in current risk identification is explored. The book goes on to cover management processes, providing a systematic analytical approach to mitigate subjectivity when addressing behavioral risks in projects. This book is useful to those working in the fields of Project Management, Systems Engineering, Risk Management, and Behavioral Science.
Decision Making in Service Industries: A Practical Approach
by Javier Faulin Angel A. Juan Michael J. Fry Scott E. GrasmanIn real-life scenarios, service management involves complex decision-making processes usually affected by random or stochastic variables. Under such uncertain conditions, the development and use of robust and flexible strategies, algorithms, and methods can provide the quantitative information necessary to make better business decisions. Decision M
Decision Making in Social Sciences: Between Traditions and Innovations (Studies in Systems, Decision and Control #247)
by Daniel Flaut Šárka Hošková-Mayerová Cristina Ispas Fabrizio Maturo Cristina FlautThis book explores several branches of the social sciences and their perspectives regarding their relations with decision-making processes: computer science, education, linguistics, sociology, and management. The decision-making process in social contexts is based on the analysis of sound alternatives using evaluative criteria. Therefore, this process is one that can be rational or irrational, and can be based on knowledge and/or beliefs. A decision-making process always produces a final decision, which may or may not imply prompt action, and increases the chances of choosing the best possible alternative. The book is divided into four main parts. The concepts covered in the first part, on computer science, explore how the rise of algorithms and the growth in computing power over the years can influence decision-making processes. In the second part, some traditional and innovative ideas and methods used in education are presented: compulsory schooling, inclusive schools, higher education, etc. In turn, the third part focuses on linguistics aspects, and examines how progress is manifested in language. The fourth part, on sociology, explores how society can be influenced by social norms, human interactions, culture, and religion. Management, regarded as a science of the decision-making process, is explored in the last part of this book. Selected organizations’ strategies, objectives and resources are presented, e.g., human resources, financial resources, and technological resources. The book gathers and presents, in a concise format, a broad range of aspects regarding the decision-making process in social contexts, making it a valuable and unique resource for the scientific community.
Decision Making in Systems Engineering and Management
by Gregory S. Parnell Patrick J. Driscoll Dale L. HendersonDecision Making in Systems Engineering and Management is a comprehensive textbook that provides a logical process and analytical techniques for fact-based decision making for the most challenging systems problems. Grounded in systems thinking and based on sound systems engineering principles, the systems decisions process (SDP) leverages multiple objective decision analysis, multiple attribute value theory, and value-focused thinking to define the problem, measure stakeholder value, design creative solutions, explore the decision trade off space in the presence of uncertainty, and structure successful solution implementation. In addition to classical systems engineering problems, this approach has been successfully applied to a wide range of challenges including personnel recruiting, retention, and management; strategic policy analysis; facilities design and management; resource allocation; information assurance; security systems design; and other settings whose structure can be conceptualized as a system.
Decision-making Strategies for Automated Driving in Urban Environments (Springer Theses)
by Antonio ArtuñedoThis book describes an effective decision-making and planning architecture for enhancing the navigation capabilities of automated vehicles in the presence of non-detailed, open-source maps. The system involves dynamically obtaining road corridors from map information and utilizing a camera-based lane detection system to update and enhance the navigable space in order to address the issues of intrinsic uncertainty and low-fidelity. An efficient and human-like local planner then determines, within a probabilistic framework, a safe motion trajectory, ensuring the continuity of the path curvature and limiting longitudinal and lateral accelerations. LiDAR-based perception is then used to identify the driving scenario, and subsequently re-plan the trajectory, leading in some cases to adjustment of the high-level route to reach the given destination. The method has been validated through extensive theoretical and experimental analyses, which are reported here in detail.
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.