This book provides a comprehensive overview of the most important and frequently considered optimization problems concerning cutting and packing. Based on appropriate modeling approaches for the problems considered, it offers an introduction to the related solution methods. It also addresses aspects like performance results for heuristic algorithms and bounds of the optimal value, as well as the packability of a given set of objects within a predefined container. The problems discussed arise in a wide variety of different fields of application and research, and as such, the fundamental knowledge presented in this book make it a valuable resource for students, practitioners, and researchers who are interested in dealing with such tasks.

A seminal collection of research methodology themes, this two-volume work provides a set of key scholarly developments related to robustness, allowing scholars to advance their knowledge of research methods used outside of their own immediate fields. With a focus on emerging methodologies within management, key areas of importance are dissected with chapters covering statistical modelling, new measurements, digital research, biometrics and neuroscience, the philosophy of research, computer modelling approaches and new mathematical theories, among others. A genuinely pioneering contribution to the advancement of research methods in business studies, Innovative Research Methodologies in Management presents an analytical and engaging discussion on each topic. By introducing new research agendas it aims to pave the way for increased application of innovative techniques, allowing the exploration of future research perspectives. Volume II explores a range of research methodologies including the Spatial Delphi and Spatial Shang, Virtual Reality, the Futures Polygon and Neuroscience research.

This book provides comprehensive coverage of the latest research on multiple criteria research analysis (MCDA) and related areas, gathering a collection of high-quality chapters prepared by leading scholars in the field. By covering the established streams in MCDA research and simultaneously exploring new and emerging areas of application, it offers a unique reference resource for the future development of MCDA. The book approaches MCDA as one of the most active areas in operations research and management science (OR/MS). It presents not only the significant advances achieved to date, but also the new opportunities and challenges arising for both the theory and practice of MCDA. Among many others, the book addresses behavioral and conceptual aspects of decision aiding and decision making, problem structuring issues in the framework of new technological and socio-economic advances, methodological and algorithmic advances for analytical modeling and decision aiding, as well as a number of new application areas in engineering, business, and the social sciences.

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 systematic introduction to the clustering algorithms for intuitionistic fuzzy values, the latest research results in intuitionistic fuzzy aggregation techniques, the extended results in interval-valued intuitionistic fuzzy environments, and their applications in multi-attribute decision making, such as supply chain management, military system performance evaluation, project management, venture capital, information system selection, building materials classification, and operational plan assessment, etc.

This is a management oriented book about efficiency, quality and effectiveness designed for an audience of management practitioners, scholars, and students. The integrative approach developed in this book contains new ideas regarding quality and efficiency-based effective management. These ideas lend themselves to managerial applications. This work is not meant to provide an exhaustive account of the measurement, and applications of effectiveness, quality, and efficiency concepts. With the exception of the treatment of conventional productivity concepts and measurements in Chapter 2, and of production flexibility in Chapter 5, the discussion in this book is largely non-teclmical. Among management practitioners, the book may be of particular interest to managers with broad strategic orientations in the fields of production management, quality management, marketing, and management of human resources. The academic audience is likely to include scholars and students interested in strategic planning, applied productivity analysis, quality management, marketing management, and management of human resources. The book could also be used as a supplementary text to or part of the readings in basic and advanced courses in strategic management, production management, and quality management. Concepts and dimensions of efficiency, quality, and effectiveness, as used throughout this book, are introduced in Chapter 1. The intricate sets of relationships among effectiveness, quality, and efficiency are explored.

Model Management and Analytics for Large Scale Systems covers the use of models and related artefacts (such as metamodels and model transformations) as central elements for tackling the complexity of building systems and managing data. With their increased use across diverse settings, the complexity, size, multiplicity and variety of those artefacts has increased. Originally developed for software engineering, these approaches can now be used to simplify the analytics of large-scale models and automate complex data analysis processes. Those in the field of data science will gain novel insights on the topic of model analytics that go beyond both model-based development and data analytics. This book is aimed at both researchers and practitioners who are interested in model-based development and the analytics of large-scale models, ranging from big data management and analytics, to enterprise domains. The book could also be used in graduate courses on model development, data analytics and data management.

This book highlights quantitative risk assessment and modeling methods for assessing health risks caused by air pollution, as well as characterizing and communicating remaining uncertainties. It shows how to apply modern data science, artificial intelligence and machine learning, causal analytics, mathematical modeling, and risk analysis to better quantify human health risks caused by environmental and occupational exposures to air pollutants. The adverse health effects that are caused by air pollution, and preventable by reducing it, instead of merely being statistically associated with exposure to air pollution (and with other many conditions, from cold weather to low income) have proved to be difficult to quantify with high precision and confidence, largely because correlation is not causation. This book shows how to use recent advances in causal analytics and risk analysis to determine more accurately how reducing exposures affects human health risks. Quantitative Risk Analysis of Air Pollution Health Effects is divided into three parts. Part I focuses mainly on quantitative simulation modelling of biological responses to exposures and resulting health risks. It considers occupational risks from asbestos and crystalline silica as examples, showing how dynamic simulation models can provide insights into more effective policies for protecting worker health. Part II examines limitations of regression models and the potential to instead apply machine learning, causal analysis, and Bayesian network learning methods for more accurate quantitative risk assessment, with applications to occupational risks from inhalation exposures. Finally, Part III examines applications to public health risks from air pollution, especially fine particulate matter (PM2.5) air pollution. The book applies freely available browser analytics software and data sets that allow readers to download data and carry out many of the analyses described, in addition to applying the techniques discussed to their own data. http://cox-associates.com:8899/

This book identifies the responsibilities of management in the regulatory territories of the FAA (USA), the EASA (European Union) and the GCAA (UAE), identifying the daily challenges of leadership in ensuring their company is meeting the regulatory obligations of compliance, safety and security that will satisfy the regulator while also meeting the fiducial responsibilities of running an economically viable and efficient lean company that will satisfy the shareholders.

Detailing each responsibility of the Accountable Manager, the author breaks them down to understandable and achievable elements where methods, systems and techniques can be applied to ensure the role holder is knowledgeable of accountabilities and is confident that they are not only compliant with the civil aviation regulations but also running an efficient and effective operation. This includes the defining of an Accountable Manager "tool kit" as well as possible software "dashboards" that focus the Accountable Manager on the important analytics, such as the information and data available, as well as making the maximum use of their expert post holder team.

This book will be of interest to leadership of all aviation- related companies, such as airlines, charter operators, private and executive operators, flying schools, aircraft and component maintenance facilities, aircraft manufacturers, engine manufacturers, component manufacturers, regulators, legal companies, leasing companies, banks and finance houses, departments of transport, etc; any relevant organisation regulated and licensed by civil aviation authority. It can also be used by students within a wide range of aviation courses at colleges, universities and training academies.

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.

The Japan Association of Simulation & Gaming (JASAG) and the Science Council of Japan (SCJ) hosted ISAGA 2003, the 34th annual conference of the International Simulation and Gaming Association (ISAGA), at Kazusa Akademia Park in Kisarazu, Japan,August 25-29, 2003. About 450 participants and guests attended,with 330 from Japan and 101 from 34 other countries. The number of submitted papers and reports exceeded 210, and in addition, many poster presentations and experiential sessions were held. This book is made up of 30 papers submitted to ISAGA 2003 and provides a good example of the diverse scope and standard of research achieved in simu- tion and gaming today.The theme of ISAGA 2003 was "Social Contributions and Responsibilities of Simulation and Gaming." Looking back over the history of simulation and gaming research in Japan,in 1991 JASAG hosted ISAGA 1991 in Kyoto. However,even though there were only 12 years between ISAGA 1991 and ISAGA 2003,and both conferences were held in the same country,Japan,for Japanese researchers,the meaning of hosting these two international conferences of simulation and gaming research was very different.

This book demonstrates what kind of problems, originating in a management accounting setting, may be solved with game theoretic models. Game theory has experienced growing interest and numerous applications in the field of management accounting. The main focus traditionally has been on the field of non-cooperative behaviour, but the area of cooperative game theory has developed rapidly and has received increasing attention. Intensive research, in combination with the changing culture of publishing, has produced a nearly unmanageable number of publications in the areas concerned. Therefore, one main purpose of this volume is providing an intensive analysis of the intersection of these areas. In addition, the book strengthens the relationship between the theory and the practical applications and it illustrates the two-sided relationship between game theory and management accounting: new game theoretic models offer new fields of applications and these applications raise new questions for the theory.

This book presents recent developments and results found by participants of the Third International Conference on the Dynamics of Information Systems, which took place at the University of Florida, Gainesville FL, USA on February 16-18, 2011. The purpose of this conference was to bring together scientists and engineers from industry, government, and universities to exchange knowledge and results in a broad range of topics relevant to the theory and practice of the dynamics of information systems.

Dynamics of Information plays an increasingly critical role in our society. The influence of information on social, biological, genetic, and military systems must be better understood to achieve large advances in the capability and understanding of these systems. Applications are widespread and include: research in evolutionary theory, optimization of information workflow, military applications, climate networks, collision work, and much more.

Dynamics of Information plays an increasingly critical role in our society. The influence of information on social, biological, genetic, and military systems must be better understood to achieve large advances in the capability and understanding of these systems. Applications are widespread and include: research in evolutionary theory, optimization of information workflow, military applications, climate networks, collision work, and much more.

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.

With the beginning of the twentieth century, American corporations in the chemical and electrical industries began establishing industrial research laboratories. Some went on to become world-famous not only for their scientific and technological breakthroughs but also for the new union of science and industry they represented. Innovative ideas do not simply appear out of the blue and spread on their own merit. Rather, the laboratory's diffusion takes place in a cultural context that goes beyond corporate capital and technological change. Using discourse analysis as a method to comprehensively capture the organizational field of the early American R&D laboratories from 1870 to 1930, this book uncovers the collective meanings associated with the industrial laboratory. Meanings such as what and where a laboratory is supposed to be, who the scientist is, and what it means to practice science provided cultural resources that made the transfer of the laboratory from academic science into an industrial setting possible by rendering such meanings understandable and operable to big business and organizational entrepreneurs fighting for hegemony in a rapidly evolving market. It analyzes not only the corporations that established laboratories in the United States but also their contexts - economic, political, and especially scientific - showing how "the industrial laboratory" was transformed from an organizational novelty into an expected institution in less than two decades. This book will be of interest to researchers, academics, historians, and students in the fields of organizational change, discourse studies, the management of technology and innovation, as well as business and management history.

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.

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.

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.

One current challenge of conducting research from the leadership-as-practice perspective is a practical one: how to capture and analyse the elusive practice of leadership within the web of mundane organising processes. Although a number of researchers have attempted to address the issue, there is not yet a definitive 'how to' guide to making sense of the empirical manifestations of leadership practices. The book responds directly to this challenge and offers a theoretical framework and practical guidance to capturing, identifying and analysing evidence of leadership practice emergence; and provides implications of this approach for leadership academics and practitioners. The developed framework enables a method for understanding these leadership instances as they are enacted by individuals within and against the evolving activities of their day-to-day work. The framework is underpinned by cultural-historical activity theory and critical realism and it conceptualises leadership practice by placing agents' actions and interactions within the context of their relationships, objectives, experiences, material and non-material artefacts and wider organising processes and organisational structures; work that has not yet been undertaken in the field. It offers a strong theoretical foundation for further development of our understanding of leadership-as-practice, providing a methodological guidance for undertaking leadership-as-practice research, and enables a discussion on the variety of underlying processes and elements as they emerge from empirical observations. It will be of value to researchers, academics, professionals, and students in the fields of business and management with a particular interest in management theory, organisational studies, and leadership research.

Sustainable Self-Governance in Businesses and Society offers a sound introduction to Stafford Beer's Viable System Model (VSM) and clarifies its relevance to support organisational sustainability and self-governance. While the VSM has been known since the early 1980s, it hasn't been always easy to understand and to apply. It explains the self-transformation methodology to analyse the way organisations manage (or not) their complexity and govern themselves. The work is supported by multiple examples of application in organisations of all scales - from small to multi-national corporations and from organised social networks to communities and national organisations. It clarifies the relevance of Beer's theory to support systemic learning and change in organisations, and to coach them to self-organise and self-govern. Readers interested in further understanding insights from complex systems and cybernetics theories for designing and transforming organisations will benefit from this book, as it works to offer very detailed insights on how to put the VSM theory into practice. It clarifies how it improves adaptive capabilities, agile and self-regulated structures, more capable of fully implementing corporate sustainability strategies and self-governing themselves. The chapters provide key reading for managers, consultants, practitioners, and post-graduate students working in organisational transformation, governance, and sustainability.

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.

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.

Certain consultants argue leaders can quickly, easily, and considerably alter their organization cultures to improve performance. Conversely, field researchers have described situations where leaders could do little to alter the existing organization culture. Between these extreme positions, a spectrum of varying degrees of leader influence exists, and organizations fall at various places along this spectrum. This book presents five field studies dealing with team, service, and sales cultures where both expected and unexpected outcomes arose. In multiple instances, leaders hoped showing some employee appreciation would compensate for offering below market average wages. Several leadership groups were prospering based on cost cuts or increased sales. Those below often had their work intensified and they were experiencing greater stress. Eight paradoxical situations were uncovered and the interpretations of the participants were based in part on their personal work histories and the history of their current organization. In each case, evidence of employee informal organization and managerial operating cultures were documented. Analyzing Organization Cultures uses detailed case studies of five work organizations to offer a comparative approach to analyzing organizational culture. It shows the latest state of knowledge on the topic and will be of interest to researchers, academics, and students in the fields of organizational studies, management history, human resource management, and organizational theory.