Computational Optimization: A Tribute to Olvi Mangasarian serves as an excellent reference, providing insight into some of the most challenging research issues in the field. This collection of papers covers a wide spectrum of computational optimization topics, representing a blend of familiar nonlinear programming topics and such novel paradigms as semidefinite programming and complementarity-constrained nonlinear programs. Many new results are presented in these papers which are bound to inspire further research and generate new avenues for applications. An informal categorization of the papers includes: Algorithmic advances for special classes of constrained optimization problems Analysis of linear and nonlinear programs Algorithmic advances B- stationary points of mathematical programs with equilibrium constraints Applications of optimization Some mathematical topics Systems of nonlinear equations.

Operations research tools are ideally suited to providing solutions and insights for the many problems health policy-maker's face. Indeed, a growing body of literature on health policy analysis, based on operations research methods, has emerged to address the problems mentioned above and several others. The research in this field is often multi-disciplinary, being conducted by teams that include not only operations researchers but also clinicians, economists and policy analysts. The research is also often very applied, focusing on a specific question driven by a decision-maker and many times yielding a tool to assist in future decisions. The goal of this volume was to bring together a group of papers by leading experts that could showcase the current state of the field of operations research applied to health-care policy. There are 18 chapters that illustrate the breadth of this field. The chapters use a variety of techniques, including classical operations research tools, such as optimization, queuing theory, and discrete event simulation, as well as statistics, epidemic models and decision-analytic models. The book spans the field and includes work that ranges from highly conceptual to highly applied. An example of the former is the chapter by Kimmel and Schackman on building policy models, and an example of the latter is the chapter by Coyle and colleagues on developing a Markov model for use by an organization in Ontario that makes recommendations about the funding of new drugs. The book also includes a mix of review chapters, such as the chapter by Hutton on public health response to influenza outbreaks, and original research, such as the paper by Blake and colleagues analyzing a decision by Canadian Blood Services to consolidate services. This volume could provide an excellent introduction to the field of operations research applied to health-care policy, and it could also serve as an introduction to new areas for researchers already familiar with the topic. The book is divided into six sections. The first section contains two chapters that describe several different applications of operations research in health policy and provide an excellent overview of the field. Sections 2 to 4 present policy models in three focused areas. Section 5 contains two chapters on conceptualizing and building policy models. The book concludes in Section 6 with two chapters describing work that was done with policy-makers and presenting insights gained from working directly with policy-makers.

Balk argues that most professionals in government agencies are underutilized. He proposes an operational approach, called public agency democracy, that should help reduce costly and disconcerting errors. The book will interest those who wish to better understand the frustrations of public service and how to turn these to motivate change.

Well over two million very qualified individuals mediate between high-level managers and other members of public agencies. These grossly underutilized intermediary professionals must become more empowered to reduce waste, malfeasance and other costly errors. Balk proposes an applied theory of public agency democracy designed to liberate the potential of its highly trained experts.

The book begins by discussing professionals as power intermediaries and their necessary tensions with authority around matters of reform. Recognized dilemmas in the field of public administration are reviewed to demonstrate the need to resolve issues concerning public agency democracy. A model is then developed to incorporate democratic action with responses ranging from routine to whistle-blowing activities. The second part of the book shows why existing management orientations are not receptive to the need for agency democracy. Conventional orientations reject the paradoxical realities of government environments; therefore, ingrained beliefs about effectiveness and management authority are at times inappropriate. Management approaches to public service motivation lack sophistication. Four final chapters are devoted to techniques and approaches on the part of professionals to initiate change. These involve techniques to assess organizational predicaments, design resolutions and become constructively involved in processes of agency reform. Ways are proposed for professionals and others to institutionalize public agency democracy in government environments.

This handbook covers various areas of Higher Education (HE) in which operations research/management science (OR/MS) techniques are used. Key examples include: international comparisons, university rankings, and rating academic efficiency with Data Envelopment Analysis (DEA); formulating academic strategy with balanced scorecard; budgeting and planning with linear and quadratic models; student forecasting; E-learning evaluation; faculty evaluation with questionnaires and multivariate statistics; marketing for HE; analytic and educational simulation; academic information systems; technology transfer with systems analysis; and examination timetabling. Overviews, case studies and findings on advanced OR/MS applications in various functional areas of HE are included.

Cognition-driven decision support system (DSS) has been recognized as a paradigm in the research and development of business intelligence (BI). Cognitive decision support aims to help managers in their decision making from human cognitive aspects, such as thinking, sensing, understanding and predicting, and fully reuse their experience. Among these cognitive aspects, decision makers situation awareness (SA) and mental models are considered to be two important prerequisites for decision making, particularly in ill-structured and dynamic decision situations with uncertainties, time pressure and high personal stake. In today s business domain, decision making is becoming increasingly complex. To make a successful decision, managers SA about their business environments becomes a critical factor.

This book presents theoretical models as well practical techniques of cognitiondriven DSS. It first introduces some important concepts of cognition orientation in decision making process and some techniques in related research areas including DSS, data warehouse and BI, offering readers a preliminary for moving forward in this book. It then proposes a cognition-driven decision process (CDDP) model which incorporates SA and experience (mental models) as its central components. The goal of the CDDP model is to facilitate cognitive decision support to managers on the basis of BI systems. It also presents relevant techniques developed to support the implementation of the CDDP model in a BI environment. Key issues addressed of a typical business decision cycle in the CDDP model include: natural language interface for a manager s SA input, extraction of SA semantics, construction of data warehouse queries based on the manger s SA and experience, situation information retrieval from data warehouse, how the manager perceives situation information and update SA, how the manager s SA leads to a final decision. Finally, a cognition-driven DSS, FACETS, and two illustrative applications of this system are discussed."

The authors contend that current knowledge management efforts in organizations need to be re-focused so that they can be better poised for success. Topics discussed include: missing capabilities of knowledge management, knowledge management in strategic alliances, customer knowledge management, knowledge markets, and knowledge management systems, among others. The authors take a pragmatic approach to knowledge management and present the material in a jargon free and accessible way.

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 introduces readers to the main traffic flow modelling approaches and discusses their features and applications. It provides a comprehensive and cutting-edge review of traffic flow models, from their roots in the 1930s to the latest developments in the field. In addition, it presents problem sets that offer readers further insights into the models and hands-on experience with simulation approaches. The simulations used in the exercises can be built upon for readers' own research or other applications. The models discussed in this book are applied to describe, predict and control traffic flows on roads with the aid of rapid and accurate estimations of current and future states. The book shows how these models are developed, what their chief characteristics are, and how they can be effectively employed.

- Authoritative but highly accessible introduction to the underlying economics of airports, their role, regulation and implications. - Written for all aviation managers, relevant local authorities and regulators, as well as serving as teaching material for air transport Masters programmes. - The book uniquely offers economic analysis and presents facts in the context of economic reasoning with clear policy recommendations.

In the industrial world, companies are always seeking competitive advantages to sustain themselves in the globalized market. A supply chain is one of these improvements that managers implement in order to stay ahead of the competition. However, certain methods of supply chains add risks such as the addition of costs, possible accidents, and economic losses. Because of this, companies are looking for techniques in which to progress their supply chain execution. The Handbook of Research on Industrial Applications for Improved Supply Chain Performance is a pivotal reference source that identifies techniques, tools, and methodologies that can improve supply chain performance and enable businesses to generate a competitive advantage in the globalized market. While highlighting topics such as material flow, route optimization, and green distribution, this publication is ideally designed for managers, executives, logistics engineers, production managers, warehouse operations managers, board directors, consultants, analysts, inventory control managers, researchers, academicians, industrial and managerial professionals, practitioners, and students looking to improve costs and quality of supply chains.

Biomarker discovery is an important area of biomedical research that may lead to significant breakthroughs in disease analysis and targeted therapy. Biomarkers are biological entities whose alterations are measurable and are characteristic of a particular biological condition. Discovering, managing, and interpreting knowledge of new biomarkers are challenging and attractive problems in the emerging field of biomedical informatics. This volume is a collection of state-of-the-art research into the application of data mining to the discovery and analysis of new biomarkers. Presenting new results, models and algorithms, the included contributions focus on biomarker data integration, information retrieval methods, and statistical machine learning techniques. This volume is intended for students, and researchers in bioinformatics, proteomics, and genomics, as well engineers and applied scientists interested in the interdisciplinary application of data mining techniques.

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.

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.

All project stakeholders have different needs, objectives, responsibilities and priorities. For many project managers it is disturbing to realise that, for any number of personal or professional reasons, some of their stakeholders may not be as co-operative and helpful as they expect. It could be a negative and powerful sponsor (the 'Anti-sponsor'), a demotivated team, low-maturity or unrealistic external clients, maliciously compliant gatekeepers and finance teams, or uninterested internal customers. The reality of project management is that stakeholders can be difficult! Jake Holloway, Professor David Bryde and Roger Joby bring their years of project management experience and combine it with research and insight from social psychology to delve into how and why project stakeholders can be difficult. The book describes some of the common stakeholder types - such as Sponsors, the Team, Gatekeepers, Clients and Contractors - and associated unhelpful or difficult behaviour profiles that you will often come across on projects. It then provides practical ideas, techniques and methods that will help the project manager to effectively manage the impact of these stakeholders on the project. As projects get larger and more complicated, the role and influence of stakeholders grows too. A Practical Guide to Dealing with Difficult Stakeholders will provide your project teams with the basis for a more sophisticated and resilient approach to stakeholder management.

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.

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 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 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 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/

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.

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.

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.

In this book . . . Nicolas Vandeput hacks his way through the maze of quantitative supply chain optimizations. This book illustrates how the quantitative optimization of 21st century supply chains should be crafted and executed. . . . Vandeput is at the forefront of a new and better way of doing supply chains, and thanks to a richly illustrated book, where every single situation gets its own illustrating code snippet, so could you. --Joannes Vermorel, CEO, Lokad Inventory Optimization argues that mathematical inventory models can only take us so far with supply chain management. In order to optimize inventory policies, we have to use probabilistic simulations. The book explains how to implement these models and simulations step-by-step, starting from simple deterministic ones to complex multi-echelon optimization. The first two parts of the book discuss classical mathematical models, their limitations and assumptions, and a quick but effective introduction to Python is provided. Part 3 contains more advanced models that will allow you to optimize your profits, estimate your lost sales and use advanced demand distributions. It also provides an explanation of how you can optimize a multi-echelon supply chain based on a simple-yet powerful-framework. Part 4 discusses inventory optimization thanks to simulations under custom discrete demand probability functions. Inventory managers, demand planners and academics interested in gaining cost-effective solutions will benefit from the "do-it-yourself" examples and Python programs included in each chapter.

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.