This book provides research results and shares experiences in the area of supply chain management. It addresses topics such as risk reduction of lesser marginal profits, disrupted supply chain management, and potential points of business failure. This book explores the "new normal" of the business supply chain. The didactic approach informs global enterprises on how to deal with the most significant issues in the current supply chain management. The book shows an in-depth analysis of post-COVID opportunities and challenges and acts as an initiative for readers to understand the risks, opportunities, and concerns resulting from the pandemic situation and is a key driver for business management among industry professionals and enterprises. Readers will learn new insights and procedures to better manage multitier supply chains, predictability, and estimation of binding capacity. The book details modeling and technology-based customer demand and response management solutions. New techniques, methods, and perspectives dealing with the estimation, acceleration or deceleration, and flexibility of logistics capacity are particularly emphasized throughout the manuscript. Real-world cases dealing with various aspects of the new normal for supply chains are analyzed. The book is useful for industry professionals and enterprise firms in business management to effectively understand risks, opportunities, and concerning the pandemic situation.

This book offers a comprehensive and readable introduction to modern business and data analytics. It is based on the use of Excel, a tool that virtually all students and professionals have access to. The explanations are focused on understanding the techniques and their proper application, and are supplemented by a wealth of in-chapter and end-of-chapter exercises. In addition to the general statistical methods, the book also includes Monte Carlo simulation and optimization. The second edition has been thoroughly revised: new topics, exercises and examples have been added, and the readability has been further improved. The book is primarily intended for students in business, economics and government, as well as professionals, who need a more rigorous introduction to business and data analytics - yet also need to learn the topic quickly and without overly academic explanations.

This new 4th edition offers an introduction to optimal control theory and its diverse applications in management science and economics. It introduces students to the concept of the maximum principle in continuous (as well as discrete) time by combining dynamic programming and Kuhn-Tucker theory. While some mathematical background is needed, the emphasis of the book is not on mathematical rigor, but on modeling realistic situations encountered in business and economics. It applies optimal control theory to the functional areas of management including finance, production and marketing, as well as the economics of growth and of natural resources. In addition, it features material on stochastic Nash and Stackelberg differential games and an adverse selection model in the principal-agent framework. Exercises are included in each chapter, while the answers to selected exercises help deepen readers' understanding of the material covered. Also included are appendices of supplementary material on the solution of differential equations, the calculus of variations and its ties to the maximum principle, and special topics including the Kalman filter, certainty equivalence, singular control, a global saddle point theorem, Sethi-Skiba points, and distributed parameter systems. Optimal control methods are used to determine optimal ways to control a dynamic system. The theoretical work in this field serves as the foundation for the book, in which the author applies it to business management problems developed from his own research and classroom instruction. The new edition has been refined and updated, making it a valuable resource for graduate courses on applied optimal control theory, but also for financial and industrial engineers, economists, and operational researchers interested in applying dynamic optimization in their fields.

Many interesting and important results on stochastic scheduling problems have been developed in recent years, with the aid of probability theory. This book provides a comprehensive and unified coverage of studies in stochastic scheduling. The objective is two-fold: (i) to summarize the elementary models and results in stochastic scheduling, so as to offer an entry-level reading material for students to learn and understand the fundamentals of this area and (ii) to include in details the latest developments and research topics on stochastic scheduling, so as to provide a useful reference for researchers and practitioners in this area. Optimal Stochastic Scheduling is organized into two parts: Chapters 1-4 cover fundamental models and results, whereas Chapters 5-10 elaborate on more advanced topics. More specifically, Chapter 1 provides the relevant basic theory of probability and then introduces the basic concepts and notation of stochastic scheduling. In Chapters 2 and 3, the authors review well-established models and scheduling policies, under regular and irregular performance measures, respectively. Chapter 4 describes models with stochastic machine breakdowns. Chapters 5 and 6 introduce, respectively, the optimal stopping problems and the multi-armed bandit processes, which are necessary for studies of more advanced subjects in subsequent chapters. Chapter 7 is focused on optimal dynamic policies, which allow adjustments of policies based on up-to-date information. Chapter 8 describes stochastic scheduling with incomplete information in the sense that the probability distributions of random variables contain unknown parameters, which can however be estimated progressively according to updated information. Chapter 9 is devoted to the situation where the processing time of a job depends on the time when it is started. Lastly, in Chapter 10 the authors look at several recent models beyond those surveyed in the previous chapters.

Parallel Scientific Computing and Optimization introduces new developments in the construction, analysis, and implementation of parallel computing algorithms. This book presents 23 self-contained chapters, including survey chapters and surveys, written by distinguished researchers in the field of parallel computing. Each chapter is devoted to some aspects of the subject: parallel algorithms for matrix computations, parallel optimization, management of parallel programming models and data, with the largest focus on parallel scientific computing in industrial applications.

This volume is intended for scientists and graduate students specializing in computer science and applied mathematics who are engaged in parallel scientific computing.

This volume represents the refereed proceedings of the Eighth International C- ference on Monte Carlo and Quasi-Monte Carlo Methods in Scienti c Computing, which was held at the University of Montreal, from 6-11 July, 2008. It contains a limited selection of articles based on presentations made at the conference. The program was arranged with the help of an international committee consisting of: Ronald Cools, Katholieke Universiteit Leuven Luc Devroye, McGill University Henri Faure, CNRS Marseille Paul Glasserman, Columbia University Peter W. Glynn, Stanford University Stefan Heinrich, University of Kaiserslautern Fred J. Hickernell, Illinois Institute of Technology Aneta Karaivanova, Bulgarian Academy of Science Alexander Keller, mental images GmbH, Berlin Adam Kolkiewicz, University of Waterloo Frances Y. Kuo, University of New South Wales Christian Lecot, Universite de Savoie, Chambery Pierre L'Ecuyer, Universite de Montreal (Chair and organizer) Jun Liu, Harvard University Peter Mathe, Weierstrass Institute Berlin Makoto Matsumoto, Hiroshima University Thomas Muller-Gronbach, Otto von Guericke Universitat Harald Niederreiter, National University of Singapore Art B. Owen, Stanford University Gilles Pages, Universite Pierre et Marie Curie (Paris 6) Klaus Ritter, TU Darmstadt Karl Sabelfeld, Weierstrass Institute Berlin Wolfgang Ch. Schmid, University of Salzburg Ian H. Sloan, University of New South Wales Jerome Spanier, University of California, Irvine Bruno Tuf n, IRISA-INRIA, Rennes Henryk Wozniak ' owski, Columbia University. v vi Preface The local arrangements (program production, publicity, web site, registration, social events, etc.

Combinatorial optimisation is a ubiquitous discipline whose usefulness spans vast applications domains. The intrinsic complexity of most combinatorial optimisation problems makes classical methods unaffordable in many cases. To acquire practical solutions to these problems requires the use of metaheuristic approaches that trade completeness for pragmatic effectiveness. Such approaches are able to provide optimal or quasi-optimal solutions to a plethora of difficult combinatorial optimisation problems.

The application of metaheuristics to combinatorial optimisation is an active field in which new theoretical developments, new algorithmic models, and new application areas are continuously emerging. This volume presents recent advances in the area of metaheuristic combinatorial optimisation, with a special focus on evolutionary computation methods. Moreover, it addresses local search methods and hybrid approaches. In this sense, the book includes cutting-edge theoretical, methodological, algorithmic and applied developments in the field, from respected experts and with a sound perspective.

This book presents innovative and high-quality research regarding advanced decision support systems (DSSs). It describes the foundations, methods, methodologies, models, tools, and techniques for designing, developing, implementing and evaluating advanced DSSs in different fields, including finance, health, emergency management, industry and pollution control. Decision support systems employ artificial intelligence methods to heuristically address problems that are cannot be solved using formal techniques. In this context, technologies such as the Semantic Web, linked data, big data, and machine learning are being applied to provide integrated support for individuals and organizations to make more rational decisions. The book is organized into two parts. The first part covers decision support systems for industry, while the second part presents case studies related to clinical emergency management and pollution control.

This book aims to provide relevant theoretical frameworks and the latest empirical research findings in Internet of Things (IoT) in Management Science and Operations Research. It starts with basic concept and present cases, applications, theory, and potential future. The contributed chapters to the book cover wide array of topics as space permits. Examples are from smart industry; city; transportation; home and smart devices. They present future applications, trends, and potential future of this new discipline. Specifically, this book provides an interface between the main disciplines of engineering/technology and the organizational, administrative, and planning capabilities of managing IoT. This book deals with the implementation of latest IoT research findings in practice at the global economy level, at networks and organizations, at teams and work groups and, finally, IoT at the level of players in the networked environments. This book is intended for professionals in the field of engineering, information science, mathematics, economics, and researchers who wish to develop new skills in IoT, or who employ the IoT discipline as part of their work. It will improve their understanding of the strategic role of IoT at various levels of the information and knowledge organization. The book is complemented by a second volume of the same editors with practical cases.

Sample-Path Analysis of Queueing Systems uses a deterministic (sample-path) approach to analyze stochastic systems, primarily queueing systems and more general input-output systems. Among other topics of interest it deals with establishing fundamental relations between asymptotic frequencies and averages, pathwise stability, and insensitivity. These results are utilized to establish useful performance measures. The intuitive deterministic approach of this book will give researchers, teachers, practitioners, and students better insights into many results in queueing theory. The simplicity and intuitive appeal of the arguments will make these results more accessible, with no sacrifice of mathematical rigor. Recent topics such as pathwise stability are also covered in this context. The book consistently takes the point of view of focusing on one sample path of a stochastic process. Hence, it is devoted to providing pure sample-path arguments. With this approach it is possible to separate the issue of the validity of a relationship from issues of existence of limits and/or construction of stationary framework. Generally, in many cases of interest in queueing theory, relations hold, assuming limits exist, and the proofs are elementary and intuitive. In other cases, proofs of the existence of limits will require the heavy machinery of stochastic processes. The authors feel that sample-path analysis can be best used to provide general results that are independent of stochastic assumptions, complemented by use of probabilistic arguments to carry out a more detailed analysis. This book focuses on the first part of the picture. It does however, provide numerous examples that invoke stochastic assumptions, which typically are presented at the ends of the chapters.

Michael Porter is recognized as one of the top authorities on corporate strategy and business competition. The historical review of strategic management clearly shows that Porter's research has bridged up two general paradigms (before and after the 1980s) thus helping both researchers and practitioners to better understand unanticipated global changes. His two generic strategies: costs and diversification, the two interdependent strategic options, are key in the context of the competitiveness of orthodox microeconomic theory. This is where Porter went further, constructing a popular value chain concept that provides the ability to disaggregate the key activities of business process in creating products and services in terms of cost analysis and value creation. This book is a collection of seven interconnected chapters that provides a coherent understanding of Michael Porter's contribution to the field of strategic management. It addresses key changes and challenges in the global business environment. The value chain concept has become highly applicable in both theory and practice. In the book, the authors offer an original interpretation of the Porters' research on strategic management in order to unravel or simplify his key theoretical concepts. It will be of interest to researchers, academics, practitioners, and students in the fields of strategic management and international business.

Based on the 2018 International Joint Conference on Industrial Engineering and Operations Management (IJCIEOM) conference that took place in Lisbon, Portugal, this proceedings volume is the first of two focusing on mathematical applications in digital transformation. The different contributions in this volume explore topics such as health care, social technologies, mathematical programming applications, public transport services, new product development, industry 4.0, occupational safety, quality control, e-services, risk management, and supply chain management. Written by renowned scientists from around the world, this multidisciplinary volume serves as a reference on industrial engineering and operations management and as a source on current findings for researchers and students who focus in business models, digital literacy and technology in education, logistics, production and information systems, and operations management.

DEA is computational at its core and this book will be one of several books that we will look to publish on the computational aspects of DEA. This book by Zhu and Cook will deal with the micro aspects of handling and modeling data issues in modeling DEA problems. DEA's use has grown with its capability of dealing with complex service industry and the public service domain types of problems that require modeling both qualitative and quantitative data. This will be a handbook treatment dealing with specific data problems including the following: (1) imprecise data, (2) inaccurate data, (3) missing data, (4) qualitative data, (5) outliers, (6) undesirable outputs, (7) quality data, (8) statistical analysis, (9) software and other data aspects of modeling complex DEA problems. In addition, the book will demonstrate how to visualize DEA results when the data is more than 3-dimensional, and how to identify efficiency units quickly and accurately.

This edited book discusses creative and recent developments of fuzzy systems and its real-life applications of multiple criteria decision making. Keeping on the existing fuzzy sets and recent developed fuzzy sets, viz., intuitionistic fuzzy, Pythagorean fuzzy, Fermatean fuzzy, Hesitant fuzzy and multiple criteria decision approaches, this book is committed to probing the soft computing techniques and fuzzy multiple criteria decision making in favour of fuzzy intelligent system and business analytics. It also addresses novel development of fuzzy set theory as well as real-life applications of fuzzy systems. It presents challenging and useful real-world applications based on problems of decision making in various fields. The modelling and solution procedures of such real-world problems will be provided concisely although all topics start with a more developed resolution. The contributory chapters will be based on the vast research experiences of the authors in real-world decision-making problems. This book provides readers with a valuable conspectus of several decision-making problems as a reference for researchers and industrial practitioners in this field. This book will broadly cover recent development of fuzzy systems and its applications of multiple criteria decision making in the areas of management and production, manufacturing management, selections problems, group decision making, transportation and logistics, inventory control systems and interval technique/fuzzy technique (uncertainty) of the above mentioned areas.

Intelligent Speech Signal Processing investigates the utilization of speech analytics across several systems and real-world activities, including sharing data analytics, creating collaboration networks between several participants, and implementing video-conferencing in different application areas. Chapters focus on the latest applications of speech data analysis and management tools across different recording systems. The book emphasizes the multidisciplinary nature of the field, presenting different applications and challenges with extensive studies on the design, development and management of intelligent systems, neural networks and related machine learning techniques for speech signal processing.

This book provides a postgraduate audience the keys they need to understand and further develop a set of tools for the efficient computation of lower bounds and valid inequalities in integer programs and combinatorial optimization problems. After discussing the classical approaches described in the literature, the book addresses how to extend these tools to other non-standard formulations that may be applied to a broad set of applications. Examples are provided to illustrate the underlying concepts and to pave the way for future contributions.

This book offers the first introduction to the concepts, theories, and applications of pricing and revenue optimization. From the initial success of "yield management" in the commercial airline industry down to more recent successes of markdown management and dynamic pricing, the application of mathematical analysis to optimize pricing has become increasingly important across many different industries. But, since pricing and revenue optimization has involved the use of sophisticated mathematical techniques, the topic has remained largely inaccessible to students and the typical manager. With methods proven in the MBA courses taught by the author at Columbia and Stanford Business Schools, this book presents the basic concepts of pricing and revenue optimization in a form accessible to MBA students, MS students, and advanced undergraduates. In addition, managers will find the practical approach to the issue of pricing and revenue optimization invaluable. With updates to every chapter, this second edition covers topics such as estimation of price-response functions and machine-learning-based price optimization. New discussions of applications of dynamic pricing and revenue management by companies such as Amazon, Uber, and Disney, and in industries such as sports, theater, and electric power, are also included. In addition, the book provides current coverage of important applications such as revenue management, markdown management, customized pricing, and the behavioral economics of pricing.

This book presents a collection of the most current research into systemic creativity and TRIZ, engendering discussion and the exchange of new discoveries in the field. With chapters on idea generation, decision making, creativity support tools, artificial intelligence and literature based discovery, it will include a number of instruments of inventive design automation. Consisting of 15-20 chapters written by leading experts in the theory for inventive problem solving (TRIZ) and adjacent fields focused upon heuristics, the contributions will add to the method of inventive design, dialogue with other tools and methods, and teaching creativity in management education through real-life case studies.

This unique book on international business presents a critical review of the role of bounded rationality in internationalization process (IP) research. Corporate internationalization processes have been a subject of scientific debate for several decades. However, it is questionable whether behavioral research insights are sufficiently acknowledged in this academic discipline. Against this backdrop, the author critically assesses the behavioral assumptions of the Uppsala Model, which is commonly considered to be the pivotal approach in internationalization process research.

This book closely examines the concept and theory of 'future' from a multidisciplinary perspective, focusing on the practice of forecasting, especially in its interaction with complexity. It highlights the relations between forecasting, decision-making and strategy, mixing technical arguments (but minimal mathematics) with ideas from psychology and philosophy. Rich with examples, the book highlights the role of values and attitudes in deciding how to look at the future. Written in a casual but precise style that makes the ideas easily digestible, it helps corporate strategists, practicing futurists, and researchers in the field of strategy or public planning gain a fundamental perspective on the future - before starting to predict things.

Based on the 2018 International Joint Conference on Industrial Engineering and Operations Management (IJCIEOM) conference that took place in Lisbon, Portugal, this proceedings volume is the first of two focusing on mathematical applications in digital transformation. The different contributions in this volume explore topics such as modelling, simulation, logistics, innovation, sustainability, health care, supply chain, lean manufacturing, operations management, quality and digital. Written by renowned scientists from around the world, this multidisciplinary volume serves as a reference on industrial engineering and operations management and as a source on current findings for researchers and students aiming to work on industrial-related problems.

The contributions included in the volume are drawn from presentations at ODS2019 - International Conference on Optimization and Decision Science, which was the 49th annual meeting of the Italian Operations Research Society (AIRO) held at Genoa, Italy, on 4-7 September 2019. This book presents very recent results in the field of Optimization and Decision Science. While the book is addressed primarily to the Operations Research (OR) community, the interdisciplinary contents ensure that it will also be of very high interest for scholars and researchers from many scientific disciplines, including computer sciences, economics, mathematics, and engineering. Operations Research is known as the discipline of optimization applied to real-world problems and to complex decision-making fields. The focus is on mathematical and quantitative methods aimed at determining optimal or near-optimal solutions in acceptable computation times. This volume not only presents theoretical results but also covers real industrial applications, making it interesting for practitioners facing decision problems in logistics, manufacturing production, and services. Readers will accordingly find innovative ideas from both a methodological and an applied perspective.

Fundamentals and important results of vector optimization in a general setting are presented in this book. The theory developed includes scalarization, existence theorems, a generalized Lagrange multiplier rule and duality results. Applications to vector approximation, cooperative game theory and multiobjective optimization are described. The theory is extended to set optimization with particular emphasis on contingent epiderivatives, subgradients and optimality conditions. Background material of convex analysis being necessary is concisely summarized at the beginning.

This second edition contains new parts on the adaptive Eichfelder-Polak method, a concrete application to magnetic resonance systems in medical engineering and additional remarks on the contribution of F.Y. Edgeworth and V. Pareto. The bibliography is updated and includes more recent important publications.

This book develops a comprehensive approach, known as the Ranking Technique, for the assessment of decision options. It aims to provide a way of presenting a decision maker with a consistent method of making a thorough assessment of all the factors associated with complex decisions. The Ranking Technique is based on a detailed analysis of all the issues involved and presents the results in a simple manner which should be understandable by the lay public not versed in the complexities of the issues involved. Ranking Technique is illustrated by application to four major decisions that have caused controversy and one fuel resource evaluation, although it is stressed that the Technique is applicable to all decision-making situations. The study describes how technical, economic and socio-political factors can be evaluated and their significance integrated to give a comprehensive assessment of the decision options.

This book highlights cutting-edge research into emergency early warning management and decision-making for severe accidents. Using toxic gas leakages as examples, it puts forward new design methods for emergency early warning systems, as well as a systematic description of emergency early warning information communication mechanisms and characteristics of regional evacuation, based on a wide range of theories, including safety engineering, information engineering, communication, behaviorology and others. The book applies a range of methods, such as case analysis, questionnaire interviews, and multi-objective optimization modeling. Drawing on this basis, it subsequently proposes a multi-objective optimization modeling and algorithm for emergency path selection, together with an evacuation risk assessment method. Divided into six chapters prepared by an international team of researchers, the book addresses the design of early warning systems, communication and dissemination mechanisms of early warning information, characteristics of regional evacuation, multi-objective optimization of emergency paths, and evacuation risk assessment. The book offers an essential reference guide for engineering technicians and researchers in a wide range of fields, including emergency management, safety science and engineering, disaster relief engineering, and transportation optimization, as well as graduate students in related majors at colleges and universities.