This book presents innovative theories, methodologies, and techniques in the field of risk management and decision making. It introduces new research developments and provides a comprehensive image of their potential applications to readers interested in the area. The collection includes: computational intelligence applications in decision making, multi-criteria decision making under risk, risk modelling,forecasting and evaluation, public security and community safety, risk management in supply chain and other business decision making, political risk management and disaster response systems. The book is directed to academic and applied researchers working on risk management, decision making, and management information systems.

This book covers the broad range of research in stochastic models and optimization. Applications covered include networks, financial engineering, production planning and supply chain management. Each contribution is aimed at graduate students working in operations research, probability, and statistics.

This book presents comprehensive state-of-the-art theoretical analysis of the fundamental Newtonian and Newtonian-related approaches to solving optimization and variational problems. A central focus is the relationship between the basic Newton scheme for a given problem and algorithms that also enjoy fast local convergence. The authors develop general perturbed Newtonian frameworks that preserve fast convergence and consider specific algorithms as particular cases within those frameworks, i.e., as perturbations of the associated basic Newton iterations. This approach yields a set of tools for the unified treatment of various algorithms, including some not of the Newton type per se. Among the new subjects addressed is the class of degenerate problems. In particular, the phenomenon of attraction of Newton iterates to critical Lagrange multipliers and its consequences as well as stabilized Newton methods for variational problems and stabilized sequential quadratic programming for optimization. This volume will be useful to researchers and graduate students in the fields of optimization and variational analysis.

The International Conference on Health Care Systems Engineering (HCSE) provided a timely opportunity to discuss statistical analysis and operations management issues in health care delivery systems. The conference took place in Milan between May 22nd and 24th, 2013. Scientists and practitioners discussed new ideas, methods and technologies for improving the operation of health care organizations. The event and this resulting volume emphasize research in the field of health care systems engineering developed in close collaboration with clinicians. Topics applicable to researchers and practitioners include: hospital drug logistics, operating theatres, modelling and simulation in patient care and healthcare organizations, home care services.

Analysis, Control and Optimization of Complex Dynamic Systems gathers in a single volume a spectrum of complex dynamic systems related papers written by experts in their fields, and strongly representative of current research trends. Complex systems present important challenges, in great part due to their sheer size which makes it difficult to grasp their dynamic behavior, optimize their operations, or study their reliability. Yet, we live in a world where, due to increasing inter-dependencies and networking of systems, complexity has become the norm. With this in mind, the volume comprises two parts. The first part is dedicated to a spectrum of complex problems of decision and control encountered in the area of production and inventory systems. The second part is dedicated to large scale or multi-agent system problems occurring in other areas of engineering such as telecommunication and electric power networks, as well as more generic context.

On one hand, marginals are complex organizational systems. On the other hand, they are an example of elegant, applied organizational operations. In The Marginal Organization, Tafoya focuses on organizations often described as part of an informal economy, informal sector, underground economy, or unofficial economy. He presents these systems first as organizations and then as organizations operating outside of society's mainstream, as marginal organizations. He outlines a means for studying marginals so that underlying behavioral patterns can be identified, examined and, if needed, addressed.
A simple approach to a study of marginal organizations might conclude they exist simply to meet the needs of their stakeholders - they do not. Thinking of marginals as competing in the context of other organizations allows the reader the opportunity to explore new themes, such as when and how marginals may be more inventive and innovative that mainstream organizations, and what one might conclude about illegal marginals like drug pushers and prostitutes. Tafoya's newest contribution to the field of organizational study is not to be missed.

Although several monographs and edited volumes have discussed scheduling in general, most of these works survey the field by contributing a single chapter to production systems like flow shops. "Flow Shop Scheduling: Theoretical Results, Algorithms, and Applications" is solely dedicated to bringing together a huge body of knowledge on the subject, along distinct design features, in order to help scholars and practitioners easily identify problems of interest. This monograph has been organized into ten distinct flow shop systems and explores their connections. The chapters cover flow shop systems including two-machine, flexible, stochastic, and more. Outside of the traditional flow shops that require a job never revisits any stage, this book also examines the reentrant flow shop, in which a job may cycle back and be reprocessed at the same station or sequence of stations, multiple times.
The authors have made the material accessible to a broad readership, using simplified notation and revealing unifying concepts. The results unique to flow shop research should provide the seed for research in other areas of scheduling and in optimization in general.

Promptly growing demand for telecommunication services and information interchange has led to the fact that communication became one of the most dynamical branches of an infrastructure of a modern society. The book introduces to the bases of classical MDP theory; problems of a finding optimal CAC in models are investigated and various problems of improvement of characteristics of traditional and multimedia wireless communication networks are considered together with both classical and new methods of theory MDP which allow defining optimal strategy of access in teletraffic systems. The book will be useful to specialists in the field of telecommunication systems and also to students and post-graduate students of corresponding specialties.

"Hybrid Predictive Control for Dynamic Transport Problems" develops methods for the design of predictive control strategies for nonlinear-dynamic hybrid discrete-/continuous-variable systems. The methodology is designed for real-time applications, particularly the study of dynamic transport systems. Operational and service policies are considered, as well as cost reduction. The control structure is based on a sound definition of the key variables and their evolution. A flexible objective function able to capture the predictive behaviour of the system variables is described. Coupled with efficient algorithms, mainly drawn from area of computational intelligence, this is shown to optimize performance indices for real-time applications. The framework of the proposed predictive control methodology is generic and, being able to solve nonlinear mixed integer optimization problems dynamically, is readily extendable to other industrial processes.

The main topics of this book are:

. hybrid predictive control (HPC) design based on evolutionary multiobjective optimization (EMO);

. HPC based on EMO for dial-a-ride systems; and

. HPC based on EMO for operational decisions in public transport systems.

"Hybrid Predictive Control for Dynamic Transport Problems" is a comprehensive analysis of HPC and its application to dynamic transport systems. Introductory material on evolutionary algorithms is presented in summary in an appendix. The text will be of interest to control and transport engineers working on the operational optimization of transport systems and to academic researchers working with hybrid systems. The potential applications of the generic methods presented here to other process fields will make the book of interest to a wider group of researchers, scientists and graduate students working in other control-related disciplines."

These proceedings focus on selected aspects of the current and upcoming trends in transportation, logistics, supply chain management, and decision sciences. In detail the included scientific papers analyze the problem of Decision Making under Uncertainty, Stochastic Optimization, Transportation, Logistics and Intelligent Business. The variety of the papers delivers added value for both scholars and practitioners. This book is the documentation of the symposium "The Seventh International Forum on Decision Sciences", which took place in Windsor, Canada.

Models & Methods for Project Selection systematically examines in this book treatment the latest work in the field of project selection modeling. The models presented are drawn from mathematical programming, decision theory, and finance. These models are examined in two categorical streams: the management science stream and the financial model stream. The book describes the assumptions and limitations of each model and provides appropriate solution methodologies. Its organization follows three main themes:
*Criteria for Choice: Chapters 1-3 investigate the effect of the choice of optimization criteria on the results of the portfolio optimization problem.
*Risk and Uncertainty: Chapters 4-7 deal with uncertainty in the project selection problem.
*Non-Linearity and Interdependence: These chapters deal with problems of non-linearity and interdependence as they arise in the project selection problem. Chapters 8, 9 and 10 present solution methodologies, which can be used to solve these most general project selection models.

This volume consists of eight papers on new advances in interpolation theory for matrix functions and completion theory for matrices and operators. Much emphasis is placed on different interpolation and completion problems when the interpolant is estimated in two different norms. The book also focusses on the study of the spectra of different completions of 2 x 2 block matrices when originally all entries are specified except the lower left corner. A third theme concerns two-sided tangential interpolation problems for real rational matrix functions, and also for the time varying case. A tangential moment problem is also analyzed. All papers deal with related problems of modern matrix analysis, operator theory, complex analysis and system theory and will appeal to a wide group of mathematicians and engineers. The material can be used for advance courses and seminars. Contents: Editorial Introduction ? D. Alpay/P. Loubaton: The tangential trigonometric moment problem on an interval and related topics ? M. Bakonyi/V.G. Kaftal/G. Weiss/H.J. Woerdeman: Maximum entropy and joint norm bounds for operator extensions ? J.A. Ball/I. Gohberg/M.A. Kaashoek: Bitangential interpolation for input-output operators of time varying systems: the discrete time case ? J.A. Ball/I. Gohberg/L. Rodman: Two-sided tangential interpolation of real rational matrix functions ? H. Du/C. Gu: On the spectra of operator completion problems ? C. Foias/A.E. Frazho/W.S. Li: The exact H2 estimate for the central H interpolant ? A.E. Frazho/s.M. Kherat: On mixed H2 - H tangential interpolation ? I. Gohberg/C.Gu: On a completion problem for matrices

There are many good AI books. Usually they consecrate at most one or two chapters to the imprecision knowledge processing. To our knowledge this is among the few books to be entirely dedicated to the treatment of knowledge imperfection when bui- ing intelligent systems. We consider that an entire book should be focused on this important aspect of knowledge processing. The expected audience for this book - cludes undergraduate students in computer science, IT&C, mathematics, business, medicine, etc. , graduates, specialists and researchers in these fields. The subjects treated in the book include expert systems, knowledge representation, reasoning under knowledge Imperfection (Probability Theory, Possibility Theory, Belief Theory, and Approximate Reasoning). Most of the examples discussed in details throughout the book are from the medical domain. Each chapter ends with a set of carefully pe- gogically chosen exercises, which complete solution provided. Their understanding will trigger the comprehension of the theoretical notions, concepts and results. Chapter 1 is dedicated to the review of expert systems. Hence are briefly discussed production rules, structure of ES, reasoning in an ES, and conflict resolution. Chapter 2 treats knowledge representation. That includes the study of the differences between data, information and knowledge, logical systems with focus on predicate calculus, inference rules in classical logic, semantic nets and frames.

2019 marked the 85th anniversary of Heinrich Freiherr von Stackelberg's habilitation thesis "Marktform und Gleichgewicht," which formed the roots of bilevel optimization. Research on the topic has grown tremendously since its introduction in the field of mathematical optimization. Besides the substantial advances that have been made from the perspective of game theory, many sub-fields of bilevel optimization have emerged concerning optimal control, multiobjective optimization, energy and electricity markets, management science, security and many more. Each chapter of this book covers a specific aspect of bilevel optimization that has grown significantly or holds great potential to grow, and was written by top experts in the corresponding area. In other words, unlike other works on the subject, this book consists of surveys of different topics on bilevel optimization. Hence, it can serve as a point of departure for students and researchers beginning their research journey or pursuing related projects. It also provides a unique opportunity for experienced researchers in the field to learn about the progress made so far and directions that warrant further investigation. All chapters have been peer-reviewed by experts on mathematical optimization.

This pioneering book on food study pursues an interdisciplinary approach to service science and the service engineering field. Further, it highlights a range of experiments conducted at actual business sites to verify the effectiveness of the proposed methodologies and theories. In modern society, food study has become more complex, as it involves multiple fields of science. For instance, a long-lived society entails a number of problems for human beings. A balanced intake of nutrients is important for a healthy life, but in many cases, healthy food is not the most enjoyable. As such, it is important for the food industry to provide foods that are both tasty and wholesome, based on the sciences of gastronomy and nutrition. Conventional food study proceeds along the lines of a specific field such as nutrition, agriculture, or gastronomy, though it should be conducted in an interdisciplinary manner. This book covers multifaceted research on food study to respond to today's societal demands, based mainly on the natural and social sciences. It addresses a wide range of topics, including: food production management using mathematical modeling, operations research, and production engineering; evaluation of food products based on big data analysis; psychological experiments and ethnography; food products based on consumer behavior; organoleptic assessment and health improvement; design of physical dining environments using virtual reality, pedestrian debt recognition (human indoor position measuring), and observation of behavior. Reporting on and assessing many studies conducted at actual business locations, the book offers a unique and highly practical resource.

This book offers an overview on the main modern important topics in random variables, random processes, and decision theory for solving real-world problems. After an introduction to concepts of statistics and signals, the book introduces many essential applications to signal processing like denoising, texture classification, histogram equalization, deep learning, or feature extraction. The book uses MATLAB algorithms to demonstrate the implementation of the theory to real systems. This makes the contents of the book relevant to students and professionals who need a quick introduction but practical introduction how to deal with random signals and processes

Multistage stochastic optimization problems appear in many ways in finance, insurance, energy production and trading, logistics and transportation, among other areas. They describe decision situations under uncertainty and with a longer planning horizon. This book contains a comprehensive treatment of today's state of the art in multistage stochastic optimization. It covers the mathematical backgrounds of approximation theory as well as numerous practical algorithms and examples for the generation and handling of scenario trees. A special emphasis is put on estimation and bounding of the modeling error using novel distance concepts, on time consistency and the role of model ambiguity in the decision process. An extensive treatment of examples from electricity production, asset liability management and inventory control concludes the book.

The book focuses on a set of cutting-edge research techniques, highlighting the potential of soft computing tools in the analysis of economic and financial phenomena and in providing support for the decision-making process. In the first part the textbook presents a comprehensive and self-contained introduction to the field of self-organizing maps, elastic maps and social network analysis tools and provides necessary background material on the topic, including a discussion of more recent developments in the field. In the second part the focus is on practical applications, with particular attention paid to budgeting problems, market simulations, and decision-making processes, and on how such problems can be effectively managed by developing proper methods to automatically detect certain patterns. The book offers a valuable resource for both students and practitioners with an introductory-level college math background.

This book outlines the latest trends in the use of multicriteria analysis in agriculture by highlighting recent applications for modeling agricultural decision-making. It introduces specific case studies using multicriteria analysis as a method for selecting multiattribute discrete alternatives or solving multiobjective planning problems. The book is intended for a broad readership, including agricultural and environmental economists, engineers and all scientists whose work involves the management of agricultural resources and decision-making in agriculture. The methods and applications presented in this book cover decision-making processes in agricultural and environmental contexts. The methodologies described consider multiple criteria simultaneously in a wide range of complex decision-making contexts by taking into account multiple, conflicting criteria. Given the wide range of case studies covered, the book offers a comprehensive guide to decision-making in the agricultural context and beyond.

Grid Resource Management: State of the Art and Future Trends presents an overview of the state of the field and describes both the real experiences and the current research available today. Grid computing is a rapidly developing and changing field, involving the shared and coordinated use of dynamic, multi-institutional resources. Grid resource management is the process of identifying requirements, matching resources to applications, allocating those resources, and scheduling and monitoring Grid resources over time in order to run Grid applications as efficiently as possible.
While Grids have become almost commonplace, the use of good Grid resource management tools is far from ubiquitous because of the many open issues of the field, including the multiple layers of schedulers, the lack of control over resources, the fact that resources are shared, and that users and administrators have conflicting performance goals. These are the issues addressed in this book, in addition to elucidating the overlap with related areas including discussions of work with peer-to-peer computing, economic approaches, and operations research.
Grid Resource Management: State of the Art and Future Trends is an invaluable resource for today's user, application developer, or resource owners when working with Grid resource management systems.

This book introduces methods for uncertain multi-attribute decision making including uncertain multi-attribute group decision making and their applications to supply chain management, investment decision making, personnel assessment, redesigning products, maintenance services, military system efficiency evaluation. Multi-attribute decision making, also known as multi-objective decision making with finite alternatives, is an important component of modern decision science. The theory and methods of multi-attribute decision making have been extensively applied in engineering, economics, management and military contexts, such as venture capital project evaluation, facility location, bidding, development ranking of industrial sectors and so on. Over the last few decades, great attention has been paid to research on multi-attribute decision making in uncertain settings, due to the increasing complexity and uncertainty of supposedly objective aspects and the fuzziness of human thought. This book can be used as a reference guide for researchers and practitioners working in e.g. the fields of operations research, information science, management science and engineering. It can also be used as a textbook for postgraduate and senior undergraduate students.

"This book provides a rigorous and comprehensive coverage of transportation models and planning methods and is a must-have to anyone in the transportation community, including students, teachers, and practitioners." Moshe Ben-Akiva, Massachusetts Institute of Technology.

This volume offers the state-of-the-art research and developments in service science and related research, education and practice areas. It showcases emerging technology and applications in fields including healthcare, information technology, transportation, sports, logistics, and public services. Regardless of size and service, a service organization is a service system. Because of the socio-technical nature of a service system, a systems approach must be adopted to design, develop, and deliver services, aimed at meeting end users' both utilitarian and socio-psychological needs. Effective understanding of service and service systems often requires combining multiple methods to consider how interactions of people, technology, organizations, and information create value under various conditions. The papers in this volume highlight ways to approach such technical challenges in service science and are based on submissions from the 2018 INFORMS International Conference on Service Science.

Since the groundbreaking research of Harry Markowitz into the application of operations research to the optimization of investment portfolios, finance has been one of the most important areas of application of operations research. The use of hidden Markov models (HMMs) has become one of the hottest areas of research for such applications to finance. This handbook offers systemic applications of different methodologies that have been used for decision making solutions to the financial problems of global markets. As the follow-up to the authors' Hidden Markov Models in Finance (2007), this offers the latest research developments and applications of HMMs to finance and other related fields. Amongst the fields of quantitative finance and actuarial science that will be covered are: interest rate theory, fixed-income instruments, currency market, annuity and insurance policies with option-embedded features, investment strategies, commodity markets, energy, high-frequency trading, credit risk, numerical algorithms, financial econometrics and operational risk. Hidden Markov Models in Finance: Further Developments and Applications, Volume II presents recent applications and case studies in finance and showcases the formulation of emerging potential applications of new research over the book's 11 chapters. This will benefit not only researchers in financial modeling, but also others in fields such as engineering, the physical sciences and social sciences. Ultimately the handbook should prove to be a valuable resource to dynamic researchers interested in taking full advantage of the power and versatility of HMMs in accurately and efficiently capturing many of the processes in the financial market.

This 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.