Beginning in the mid-2010s, the Fourth Industrial Revolution has seen remarkable changes in information technology which have blurred the boundaries between the physical, digital, and biological worlds. Industry 4.0 has enabled so-called "smart factories" in which computer systems equipped with machine learning algorithms can learn and control robotics with minimal need for human input. While smart technology has enabled many manufacturing businesses to increase efficiency and cut costs, many others are still struggling with implementing it. This book aims to help students, practitioners and industry leaders to become change agents and take their first steps on the path of transformation. Smart Business and Digital Transformation addresses the challenge of becoming "smart" from three different perspectives: smart factory, smart industry, and smart environment. Covering technologies including the Internet of Things (IoT), cloud, artificial intelligence (AI), mobility, 5G, Big Data analytics, the book shows how enterprises can take advantage of them and ultimately beat the competition. The book considers the importance of operational processes, business models, and organizational culture. The contributing authors and editors, based at Corvinus University, present a multi-dimensional picture of industry 4.0 which is both diverse in its voices and unified in its vision. Smart Business and Digital Transformation meets the growing demand for a textbook that not only presents the latest concepts and theories but is also practical for planning, managing, and implementing digital transformation in practice. The chapters include case studies to demonstrate the practical applications, and each chapter ends with review and discussion questions to develop students' skills and competencies. Students of business and digital transformation on advanced undergraduate and MBA courses will find it an indispensable guide to a vibrant and challenging topic.

This Handbook is a collection of chapters on key issues in the design and analysis of computer simulation experiments on models of stochastic systems. The chapters are tightly focused and written by experts in each area. For the purpose of this volume "simulation" refers to the analysis of stochastic processes through the generation of sample paths (realization) of the processes.
Attention focuses on design and analysis issues and the goal of this volume is to survey the concepts, principles, tools and techniques that underlie the theory and practice of stochastic simulation design and analysis. Emphasis is placed on the ideas and methods that are likely to remain an intrinsic part of the foundation of the field for the foreseeable future. The chapters provide up-to-date references for both the simulation researcher and the advanced simulation user, but they do not constitute an introductory level 'how to' guide.
Computer scientists, financial analysts, industrial engineers, management scientists, operations researchers and many other professionals use stochastic simulation to design, understand and improve communications, financial, manufacturing, logistics, and service systems. A theme that runs throughout these diverse applications is the need to evaluate system performance in the face of uncertainty, including uncertainty in user load, interest rates, demand for product, availability of goods, cost of transportation and equipment failures.
* Tightly focused chapters written by experts
* Surveys concepts, principles, tools, and techniques that underlie the theory and practice of stochastic simulation design and analysis
* Provides an up-to-date reference for bothsimulation researchers and advanced simulation users

Examining the dynamics of competence-building processes at the firm level, this book looks at a sample of Japanese and European companies engaged in the field of optoelectronics. The concept was derived from the notion of firm-specific competences which are closely related to the firm's intangible assets and accumulated technological bases. Several factors affect the rate and direction of competence-building, chief among them being primary markets, top management strategy and the evolution of research and development organization, and organizational learning. The book also introduces a technique to assess competences using three types of data on US patenting, scientific publications and qualitative interview data.

The design and location of production facilities are important aspects of corporate strategy which can have a significant impact on the socio economy of nations and regions. Here, these decisions are recognized as being interrelated; that is, the optimal plant design (input mix and output level) depends on the location of the plant, and the optimal location of the plant depends on the design of the plant. Until the late 1950s, however, the questions of where a firm should locate its plant and what should be its planned input mix and output level were treated, for the most part, as separate questions, and were investigated by different groups of research ers. Although there was some recognition that these questions are inter I 1928; Hoover 1948; Isard 1956], no detailed analysis related [e. g. , Pre doh or formal structure was developed combining these two problems until the work of Moses [1958]. In recent years scholarly interest in the integrated production/locaton decision has been increasing rapidly. At the same time that research on the integrated production/location problem was expanding, significant related work was occurring in the fields of operations research, transportation science, industrial engineering, eco nomics, and geography. Unfortunately, the regional scientists working on the production/location problem had little contact with researchers in other fields. They generally publish in different journals and attend dif ferent professional meetings. Consequently, little of the recent work in these fields has made its way into the production/location research and vice versa.

In many decision problems, e.g. from the area of production and logistics manage ment, the evaluation of alternatives and the determination of an optimal or at least suboptimal solution is an important but dif?cult task. For most such problems no ef?cient algorithm is known and classical approaches of Operations Research like Mixed Integer Linear Programming or Dynamic Pro gramming are often of limited use due to excessive computation time. Therefore, dedicated heuristic solution approaches have been developed which aim at providing good solutions in reasonable time for a given problem. However, such methods have two major drawbacks: First, they are tailored to a speci?c prob lem and their adaption to other problems is dif?cult and in many cases even impos sible. Second, they are typically designed to "build" one single solution in the most effective way, whereas most decision problems have a vast number of feasible solu tions. Hence usually the chances are high that there exist better ones. To overcome these limitations, problem independent search strategies, in particular metaheuris tics, have been proposed. This book provides an elementary step by step introduction to metaheuristics focusing on the search concepts they are based on. The ?rst part demonstrates un derlying concepts of search strategies using a simple example optimization problem.

This book presents new insights and successful solutions to the operational problems of automated container terminals and cargo systems. It comprises reports on the state of the art, applications of quantitative methods, as well as case studies and simulation results. Its contributions are written by leading experts from academia and business and address practitioners and researchers in logistics, transportation, and management.

As its title implies, Advances in Multicriteria Analysis presents the most recent developments in multicriteria analysis and in some of its principal areas of application, including marketing, research and development evaluation, financial planning, and medicine. Special attention is paid to the interaction between multicriteria analysis, decision support systems and preference modeling. The five sections of the book cover: methodology; problem structuring; utility assessment; multi-objective optimisation; real world applications. Audience: Researchers and professionals who are operations researchers, management scientists, computer scientists, statisticians, decision analysts, marketing managers and financial analysts.

The increasing power of computer technologies, the evolution of software en- neering and the advent of the intelligent transport systems has prompted traf c simulation to become one of the most used approaches for traf c analysis in s- port of the design and evaluation of traf c systems. The ability of traf c simulation to emulate the time variability of traf c phenomena makes it a unique tool for capturing the complexity of traf c systems. In recent years, traf c simulation - and namely microscopic traf c simulation - has moved from the academic to the professional world. A wide variety of traf- c simulation software is currently available on the market and it is utilized by thousands of users, consultants, researchers and public agencies. Microscopic traf c simulation based on the emulation of traf c ows from the dynamics of individual vehicles is becoming one the most attractive approaches. However, traf c simulation still lacks a uni ed treatment. Dozens of papers on theory and applications are published in scienti c journals every year. A search of simulation-related papers and workshops through the proceedings of the last annual TRB meetings would support this assertion, as would a review of the minutes from speci cally dedicated meetings such as the International Symposiums on Traf c Simulation (Yokohama, 2002; Lausanne, 2006; Brisbane, 2008) or the International Workshops on Traf c Modeling and Simulation (Tucson, 2001; Barcelona, 2003; Sedona, 2005; Graz 2008). Yet, the only comprehensive treatment of the subject to be found so far is in the user's manuals of various software products.

This volume develops and describes an ontology of modern conflict. Modern conflict is a complex adaptive system. As such, it exhibits emergent properties, or properties that are not predictable from simple descriptions of the system. The Modern Conflict Ontology (MCO) creates a structure for collecting and analyzing information regarding both conventional and unconventional conflict in the face of uncertainty. The first three chapters of the book begin the discussion of the MCO. The first chapter introduces the foundational concepts. The second chapter discusses modern conflict in detail. The third chapter provides an overview of ontologies in sufficient detail to make the rest of the book understandable, but without covering the minutia of the subject. The next ten chapters describe the parts of the MCO. Each part is a sub-ontology and is discussed in detail, including connections to the other parts. Instances are used very liberally to ensure that the concepts are made concrete. The final chapter consolidates the descriptions of the ontology into a discussion of "what we can know." It describes the implementation history and changes from the predecessor Unconventional Conflict Ontology (UCO) to the MCO, plus some uses of the ontology and potential future enhancements. Providing an ontology that describes the entire modern conflict domain, this volume is appropriate for military professionals and academics and professionals in political science, computer science, and operations research.

Our everyday life is unthinkable without optimization. We try to minimize our effort and to maximize the achieved profit. Many real world and industrial problems arising in engineering, economics, medicine and other domains can be formulated as optimization tasks. This volume is a comprehensive collection of extended contributions from the Workshop on Computational Optimization 2013. It presents recent advances in computational optimization. The volume includes important real life problems like parameter settings for controlling processes in bioreactor, resource constrained project scheduling, problems arising in transport services, error correcting codes, optimal system performance and energy consumption and so on. It shows how to develop algorithms for them based on new metaheuristic methods like evolutionary computation, ant colony optimization, constrain programming and others.

This book gathers extended versions of the best papers presented at the Global Joint Conference on Industrial Engineering and Its Application Areas (GJCIE), held on September 2-3, 2019, in Gazimagusa, North Cyprus, Turkey. It covers a wide range of topics, including decision analysis, supply chain management, systems modelling and quality control. Further, special emphasis is placed on the state of the art and the challenges of digital disruption, as well as effective strategies that can be used to change organizational structures and eliminate the barriers that are keeping industries from taking full advantage of today's digital technologies.

ENERGY AND ENVIRONMENT is a volume on energy and environmental modeling that describes a broad variety of modeling methodologies, embodied in models of varying scopes and philosophies, ranging from top-down integrated assessment models to bottom-up partial equilibrium models, to hybrid models. Integrated into the discussion and examination are chapters covering:

The Sustainability of Economic Growth by Cabo, MartA-n-HerrAn & MartA-nez-GarcA-a; Abatement Scenarios in the Swiss Housing Sector by L. Drouet et al; Support and Planning for Off-Site Emergency Management, by Geldermann et al; Hybrid Energy-Economy Models, by Jaccard; The World-MARKAL Model and Its Application, by Kanudia et al; Methodology for Evaluating a Market of Tradable CO2-Permits, by Kunsch and Springael; MERGE a" A Model for Global Climate Change, by Manne and Richels; A Linear Programming Model for Capacity Expansion in an Autonomous Power Generation System, by Mavrotas and Diakoulaki; Transport and Climate Policy Modeling in the Transport Sector, by Paltsev et al; Analysis of Ontario Electricity Capacity Requirements and Emissions, by Pineau and Schott; Environmental Damage in Energy / Environmental Policy Evaluation, by Van Regemorter.

This book explores the meta-heuristics approach called tabu search, which is dramatically changing our ability to solve a host of problems that stretch over the realms of resource planning, telecommunications, VLSI design, financial analysis, scheduling, space planning, energy distribution, molecular engineering, logistics, pattern classification, flexible manufacturing, waste management, mineral exploration, biomedical analysis, environmental conservation and scores of other problems. The major ideas of tabu search are presented with examples that show their relevance to multiple applications. Numerous illustrations and diagrams are used to clarify principles that deserve emphasis, and that have not always been well understood or applied. The book's goal is to provide hands-on' knowledge and insight alike, rather than to focus exclusively either on computational recipes or on abstract themes. This book is designed to be useful and accessible to researchers and practitioners in management science, industrial engineering, economics, and computer science. It can appropriately be used as a textbook in a masters course or in a doctoral seminar. Because of its emphasis on presenting ideas through illustrations and diagrams, and on identifying associated practical applications, it can also be used as a supplementary text in upper division undergraduate courses. Finally, there are many more applications of tabu search than can possibly be covered in a single book, and new ones are emerging every day. The book's goal is to provide a grounding in the essential ideas of tabu search that will allow readers to create successful applications of their own. Along with the essential ideas, understanding of advanced issues is provided, enabling researchers to go beyond today's developments and create the methods of tomorrow.

With the ever increasing growth of services and the corresponding demand for Quality of Service requirements that are placed on IP-based networks, the essential aspects of network planning will be critical in the coming years. A wide number of problems must be faced in order for the next generation of IP networks to meet their expected performance. With Performance Evaluation and Planning Methods for the Next Generation Internet, the editors have prepared a volume that outlines and illustrates these developing trends.

A number of the problems examined and analyzed in the book are:

-The design of IP networks and guaranteed performance

-Performances of virtual private networks

-Network design and reliability

-The issues of pricing, routing and the management of QoS

-Design problems arising from wireless networks

-Controlling network congestion

-New applications spawned from Internet use

-Several new models are introduced that will lead to better Internet performance

These are a few of the problem areas addressed in the book and only a selective example of some of the coming key areas in networks requiring performance evaluation and network planning.

This volume presents selected contributions by top researchers in the field of operations research, originating from the XVI Congress of APDIO. It provides interesting findings and applications of operations research methods and techniques in a wide variety of problems. The contributions address complex real-world problems, including inventory management with lateral transshipments, sectors and routes in solid-waste collection and production planning for perishable food products. It also discusses the latest techniques, making the volume a valuable tool for researchers, students and practitioners who wish to learn about current trends. Of particular interest are the applications of nonlinear and mixed-integer programming, data envelopment analysis, clustering techniques, hybrid heuristics, supply chain management and lot sizing, as well as job scheduling problems. This biennial conference, organized by APDIO, the Portuguese Association of Operational Research, held in Braganca, Portugal, in June 2013, presented a perfect opportunity to discuss the latest development in this field and to narrow the gap between academic researchers and practitioners.

Risk models are models of uncertainty, engineered for some purposes. They are "educated guesses and hypotheses" assessed and valued in terms of well-defined future states and their consequences. They are engineered to predict, to manage countable and accountable futures and to provide a frame of reference within which we may believe that "uncertainty is tamed". Quantitative-statistical tools are used to reconcile our information, experience and other knowledge with hypotheses that both serve as the foundation of risk models and also value and price risk. Risk models are therefore common to most professions, each with its own methods and techniques based on their needs, experience and a wisdom accrued over long periods of time. This book provides a broad and interdisciplinary foundation to engineering risks and to their financial valuation and pricing. Risk models applied in industry and business, heath care, safety, the environment and regulation are used to highlight their variety while financial valuation techniques are used to assess their financial consequences. This book is technically accessible to all readers and students with a basic background in probability and statistics (with 3 chapters devoted to introduce their elements). Principles of risk measurement, valuation and financial pricing as well as the economics of uncertainty are outlined in 5 chapters with numerous examples and applications. New results, extending classical models such as the CCAPM are presented providing insights to assess the risks and their price in an interconnected, dependent and strategic economic environment. In an environment departing from the fundamental assumptions we make regarding financial markets, the book provides a strategic/game-like approach to assess the risk and the opportunities that such an environment implies. To control these risks, a strategic-control approach is developed that recognizes that many risks resulting by "what we do" as well as "what others do". In particular we address the strategic and statistical control of compliance in large financial institutions confronted increasingly with a complex and far more extensive regulation.

Discrete event simulation and agent-based modeling are increasingly recognized as critical for diagnosing and solving process issues in complex systems. Introduction to Discrete Event Simulation and Agent-based Modeling covers the techniques needed for success in all phases of simulation projects. These include: * Definition - The reader will learn how to plan a project and communicate using a charter. * Input analysis - The reader will discover how to determine defensible sample sizes for all needed data collections. They will also learn how to fit distributions to that data. * Simulation - The reader will understand how simulation controllers work, the Monte Carlo (MC) theory behind them, modern verification and validation, and ways to speed up simulation using variation reduction techniques and other methods. * Output analysis - The reader will be able to establish simultaneous intervals on key responses and apply selection and ranking, design of experiments (DOE), and black box optimization to develop defensible improvement recommendations. * Decision support - Methods to inspire creative alternatives are presented, including lean production. Also, over one hundred solved problems are provided and two full case studies, including one on voting machines that received international attention. Introduction to Discrete Event Simulation and Agent-based Modeling demonstrates how simulation can facilitate improvements on the job and in local communities. It allows readers to competently apply technology considered key in many industries and branches of government. It is suitable for undergraduate and graduate students, as well as researchers and other professionals.

Dynamic Systems (DEDS) are almost endless: military C31 Ilogistic systems, the emergency ward of a metropolitan hospital, back offices of large insurance and brokerage fums, service and spare part operations of multinational fums . . . . the point is the pervasive nature of such systems in the daily life of human beings. Yet DEDS is a relatively new phenomenon in dynamic systems studies. From the days of Galileo to Newton to quantum mechanics and cosmology of the present, dynamic systems in nature are primarily differential equations based and time driven. A large literature and endless success stories have been built up on such Continuous Variable Dynamic Systems (CVDS). It is, however, equally clear that DEDS are fundamentally different from CVDS. They are event driven, asynchronous, mostly man-made and only became significant during the past generation. Increasingly, however, it can be argued that in the modem world our lives are being impacted by and dependent upon the efficient operations of such DEDS. Yet compared to the successful paradigm of differential equations for CVDS the mathematical modelling of DEDS is in its infancy. Nor are there as many successful and established techniques for their analysis and synthesis. The purpose of this series is to promote the study and understanding of the modelling, analysis, control, and management of DEDS. The idea of the series came from editing a special issue of the Proceedings of IEEE on DEOS during 1988.

This is the first comprehensive book to present, in English, the multicriteria methodology for decision aiding. In the foreword the distinctive features and main ideas of the European School of MCDA are outlined. The twelve chapters are essentially expository in nature, but scholarly in treatment. Some questions, which are too often neglected in the literature on decision theory, such as how is a decision made, who are the actors, what is a decision aiding model, how to define the set of alternatives, are discussed. Examples are used throughout the book to illustrate the various concepts. Ways to model the consequences of each alternative and building criteria taking into account the inevitable imprecisions, uncertainties and indeterminations are described and illustrated. The three classical operational approaches of MCDA: synthesis in one criterion (including MAUT), synthesis by outranking relations, interactive local judgements, are studied. This methodology tries to be a theoretical or intellectual framework directed towards formulating recommendations for action. The book is addressed to graduate students, postgraduates and researchers in management sciences, or operations research or decision analysis, as well as all scientists who use models and methods for guiding decisions. In addition all those who, in business and administration, wish to take part in decision-making through scientific reasoning will be interested.

This book covers the latest results in the field of risk analysis. Presented topics include probabilistic models in cancer research, models and methods in longevity, epidemiology of cancer risk, engineering reliability and economical risk problems. The contributions of this volume originate from the 5th International Conference on Risk Analysis (ICRA 5). The conference brought together researchers and practitioners working in the field of risk analysis in order to present new theoretical and computational methods with applications in biology, environmental sciences, public health, economics and finance.

Each chapter in Equilibrium and Advanced Transportation Modelling develops a topic from basic concepts to the state-of-the-art, and beyond. All chapters relate to aspects of network equilibrium. Chapter One advocates the use of simulation models for the representation of traffic flow movements at the microscopic level. Chapter Two presents travel demand systems for generating trip matrices from activity-based models, taking into account the entire daily schedule of network users. Chapter Three examines equilibrium strategic choices adopted by the passengers of a congested transit system, carefully addressing line selection at boarding and transfer nodes. Chapter Four provides a critical appraisal of the traditional process that consists in sequentially performing the tasks of trip generation, trip distribution, mode split and assignment, and its impact on the practice of transportation planning. Chapter Five gives an insightful overview of stochastic assignment models, both in the static and dynamic cases. Chapters Six and Seven investigate the setting of tolls to improve traffic flow conditions in a congested transportation network. Chapter Eight provides a unifying framework for the analysis of multicriteria assignment models. In this chapter, available algorithms are summarized and an econometric perspective on the estimation of heterogeneous preferences is given. Chapter Nine surveys the use of hyperpaths in operations research and proposes a new paradigm of equilibrium in a capacitated network, with an application to transit assignment. Chapter Ten analyzes the transient states of a system moving towards equilibrium, using the mathematical framework of projected dynamical systems. Chapter Eleven discusses an in-depth survey of algorithms for solving shortest path problems, which are pervasive to any equilibrium algorithm. The chapter devotes special attention to the computation of dynamic shortest paths and to shortest hyperpaths. The final chapter considers operations research tools for reducing traffic congestion, in particular introducing an algorithm for solving a signal-setting problem formulated as a bilevel program.

The Practice of Quality Management presents the results of eleven ground-breaking research projects in quality management. It is the first collection of research papers by academics in this area. The projects are empirical studies on total quality management that suggest new ways to think about quality. The objective of the research found in this book is to develop theory and to assist practice. Thus, this volume is of interest to both academic researchers and practising managers. The chapters fall into four categories: `Performance', `Understanding TQM', `Organizations', and `Using TQM'. All of the chapters show that there are many different applications and research issues associated with quality. The chapters on `Understanding TQM' suggest that it is possible to develop and test theories of quality. The chapters on `Performance' demonstrate that studies of the operational and financial effect of quality can yield positive results. Many thinkers on quality consider that organizational impacts of quality are the most important drivers of the quality process. The chapters on `Organizations' present evidence on how quality programs affect human resource management, and organizational structure. Finally, the chapters on `Using TQM' present several studies of applications of quality management.

These proceedings consist of 30 selected research papers based on results presented at the 10th Balkan Conference & 1st International Symposium on Operational Research (BALCOR 2011) held in Thessaloniki, Greece, September 22-24, 2011. BALCOR is an established biennial conference attended by a large number of faculty, researchers and students from the Balkan countries but also from other European and Mediterranean countries as well. Over the past decade, the BALCOR conference has facilitated the exchange of scientific and technical information on the subject of Operations Research and related fields such as Mathematical Programming, Game Theory, Multiple Criteria Decision Analysis, Information Systems, Data Mining and more, in order to promote international scientific cooperation. The carefully selected and refereed papers present important recent developments and modern applications and will serve as excellent reference for students, researchers and practitioners in these disciplines. "

Operations Research and Cyber-Infrastructure is the companion volume to the Eleventh INFORMS Computing Society Conference (ICS 2009), held in Charleston, South Carolina, from January 11 to 13, 2009. It includes 24 high-quality refereed research papers.

As always, the focus of interest for ICS is the interface between Operations Research and Computer Science, and the papers in this volume reflect that interest. This is naturally an evolving area as computational power increases rapidly while decreasing in cost even more quickly. The papers included here illustrate the wide range of topics at this interface. For convenience, they are grouped in broad categories and subcategories. There are three papers on modeling, reflecting the impact of recent development in computing on that area. Eight papers are on optimization (three on integer programming, two on heuristics, and three on general topics, of which two involve stochastic/probabilistic processes). Finally, there are thirteen papers on applications (three on the conference theme of cyber-infrastructure, four on routing, and six on other interesting topics). Several of the papers could be classified in more than one way, reflecting the interactions between these topic areas.

This book presents a close look at the main developments in IT, business processes and offshore outsourcing. The authors study these topics in both theory and practice, exploring the rising prominence of outsourcing with a multi-dimensional, contextual perspective.