This book investigates in detail large-scale group decision-making (LSGDM) problem, which has gradually evolved from the traditional group decision-making problem and has attracted more and more attention in the age of big data. Pursuing a holistic approach, the book establishes a fundamental framework for LSGDM with uncertain and behavioral considerations. To address the behavioral uncertainty and complexity of large groups of decision-makers, this book mainly focuses on new solutions of LSGDM problems using the interval type-2 fuzzy uncertainty theory and social network analysis techniques, including the exploration of uncertain clustering analysis, the consideration of social relationships, especially trust relationships, the construction of consensus evolution networks, etc. The book is intended for researchers and postgraduates who are interested in complex group decision-making in the new media era. Authors also investigate the similar features between LSGDM problems and group recommendations to study the applications of LSGDM methods. After reading this book, readers will have a new understanding of the LSGDM study under the real complicated context. 

This tutorial introduces readers to several variants of routing problems with profits. In these routing problems each node has a certain profit, and not all nodes need to be visited. Since the orienteering problem (OP) is by far the most frequently studied problem in this category of routing problems, the book mainly focuses on the OP. In turn, other problems are presented as variants of the OP, focusing on the similarities and differences. The goal of the OP is to determine a subset of nodes to visit and in which order, so that the total collected profit is maximized and a given time budget is not exceeded.The book provides a comprehensive review of variants of the OP, such as the team OP, the team OP with time windows, the profitable tour problem, and the prize-collecting travelling salesperson problem. In addition, it presents mathematical models and techniques for solving these OP variants and discusses their complexity. Several simple examples and benchmark instances, together with their best-known results, are also included. Finally, the book reviews the latest applications of these problems in the fields of logistics, tourism and others.

Remarkable features of revenue management (RM) problems in the cargo, manufacturing and broadcasting industries are so-called flexible products. "Flexibility" means that the actual mode of production is not defined at the time of purchase, but can be chosen later on by the service provider. This book is among the first to analyze RM problems with flexible products and RM in broadcasting companies. The implications of flexibility are explicitly taken into account in the models and methods presented. As an aside, the book contains descriptions of algorithms to generate stochastic demand data streams for general RM problems. An implementation as a Microsoft Windows executable file is available, which can directly be used both by theoreticians and practitioners in their own simulation studies. This book will be of great value for researchers, managers and students interested in RM with flexible products in general and broadcasting companies in particular.

This book showcases how the latest and most advanced types of analytical modeling and empirical analysis can help to create value in the global supply chain. Focusing on practical relevance, it shares valuable management insights and addresses key issues in operations management (OM), demonstrating how past research has led to various practices and impacts, while also exploring the aspirations of the latest research. It presents current research on various topics such as global supply chain design, service supply chains, product design, responsible supply chains, performance and incentives in operations, data analytics in health services, new business models in the digital age, and new digital technology advances such as blockchain. In addition, it presents practical case studies on the aforementioned topics. Beyond the value of its contents, the book is intended as a tribute to Professor Morris Cohen, who has been a major contributor to advancing the research frontier in operations management and a driving force in shaping the field. Given its scope, the book will appeal to a wide readership, from researchers and PhD students to practitioners and consultants.

In Linear Programming: A Modern Integrated Analysis, both boundary (simplex) and interior point methods are derived from the complementary slackness theorem and, unlike most books, the duality theorem is derived from Farkas's Lemma, which is proved as a convex separation theorem. The tedium of the simplex method is thus avoided. A new and inductive proof of Kantorovich's Theorem is offered, related to the convergence of Newton's method. Of the boundary methods, the book presents the (revised) primal and the dual simplex methods. An extensive discussion is given of the primal, dual and primal-dual affine scaling methods. In addition, the proof of the convergence under degeneracy, a bounded variable variant, and a super-linearly convergent variant of the primal affine scaling method are covered in one chapter. Polynomial barrier or path-following homotopy methods, and the projective transformation method are also covered in the interior point chapter. Besides the popular sparse Cholesky factorization and the conjugate gradient method, new methods are presented in a separate chapter on implementation. These methods use LQ factorization and iterative techniques.

This volume results from the "Second International Conference on Dynamics of Disasters" held in Kalamata, Greece, June 29-July 2, 2015. The conference covered particular topics involved in natural and man-made disasters such as war, chemical spills, and wildfires. Papers in this volume examine the finer points of disasters through: Critical infrastructure protection Resiliency Humanitarian logistic Relief supply chains Cooperative game theory Dynamical systems Decision making under risk and uncertainty Spread of diseases Contagion Funding for disaster relief Tools for emergency preparedness Response, and risk mitigation Multi-disciplinary theories, tools, techniques and methodologies are linked with disasters from mitigation and preparedness to response and recovery. The interdisciplinary approach to problems in economics, optimization, government, management, business, humanities, engineering, medicine, mathematics, computer science, behavioral studies, emergency services, and environmental studies will engage readers from a wide variety of fields and backgrounds.

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 explores clustering operations in the context of social networks and consensus-reaching paths that take into account non-cooperative behaviors. This book focuses on the two key issues in large-scale group decision-making: clustering and consensus building. Clustering aims to reduce the dimension of a large group. Consensus reaching requires that the divergent individual opinions of the decision makers converge to the group opinion. This book emphasizes the similarity of opinions and social relationships as important measurement attributes of clustering, which makes it different from traditional clustering methods with single attribute to divide the original large group without requiring a combination of the above two attributes. The proposed consensus models focus on the treatment of non-cooperative behaviors in the consensus-reaching process and explores the influence of trust loss on the consensus-reaching process.The logic behind is as follows: firstly, a clustering algorithm is adopted to reduce the dimension of decision-makers, and then, based on the clusters' opinions obtained, a consensus-reaching process is carried out to obtain a decision result acceptable to the majority of decision-makers. Graduates and researchers in the fields of management science, computer science, information management, engineering technology, etc., who are interested in large-scale group decision-making and consensus building are potential audience of this book. It helps readers to have a deeper and more comprehensive understanding of clustering analysis and consensus building in large-scale group decision-making.

This book reviews the field of Knowledge Management, taking a holistic approach that includes both "soft" and "hard" aspects. It provides a broad perspective on the field, rather than one based on a single viewpoints from Computer Science or Organizational Learning, offering a comprehensive and integrated conception of Knowledge Management. The chapters represent the best Knowledge Management articles published in the 21st century in Knowledge Management Research & Practice and the European Journal of Information Systems, with contributors including Ikujiro Nonaka, Frada Burstein, and David Schwartz. Most of the chapters contribute significantly to practise as well as theory. The OR Essentials series presents a unique cross-section of high quality research work fundamental to understanding contemporary issues and research across a range of Operational Research topics. It brings together some of the best research papers from the highly respected journals of the Operational Research Society, also published by Palgrave Macmillan.

'A refreshing and useful addition to the folklore of management. All in all this is a worthwhile insight into the management views and structure of some of our leading construction companies.' - J.J. Farrow, Chartered Builder This volume describes and analyses the behaviour of large UK construction firms in the determination and implementation of their strategy. It covers, in addition to the selection of objectives and the methods for their achievement, policies on growth and diversification, finance, marketing and bidding, international operations, management and labour and subcontracting. Throughout the book the relationship is examined between the theory outlined in the companion volume and the actual behaviour of firms. The final chapter concludes with a discussion of the means to bridge the gaps which are found to exist between theory and practice.

This book offers a concise introduction and comprehensive overview of the state of the art in the field of decision-making and consensus modeling, with a special emphasis on fuzzy methods. It consists of a collection of authoritative contributions reporting on the decision-making process from different perspectives: from psychology to social and political sciences, from decision sciences to data mining, and from computational sciences in general, to artificial and computational intelligence and systems. Written as a homage to Mario Fedrizzi for his scholarly achievements, creative ideas and long lasting services to different scientific communities, it introduces key theoretical concepts, describes new models and methods, and discusses a range of promising real-world applications in the field of decision-making science. It is a timely reference guide and a source of inspiration for advanced students and researchers

This book addresses new concepts, methods, algorithms, modeling, and applications of green supply chain, inventory control problems, assignment problems, transportation problem, linear problems and new information related to optimization for the topic from the theoretical and applied viewpoints of neutrosophic sets and logic. The book is an innovatory of new tools and procedures, such as: Neutrosophic Statistical Tests and Dependent State Samplings, Neutrosophic Probabilistic Expert Systems, Neutrosophic HyperSoft Set, Quadripartitioned Neutrosophic Cross-Entropy, Octagonal and Spherical and Cubic Neutrosophic Numbers used in machine learning. It highlights the process of neutrosofication {which means to split the universe into three parts, two opposite ones (Truth and Falsehood), and an Indeterminate or neutral one (I) in between them}. It explains Three-Ways Decision, how the universe set is split into three different distinct areas, in regard to the decision process, representing: Acceptance, Noncommitment, and Rejection, respectively. The Three-Way Decision is used in the Neutrosophic Linguistic Rough Set, which has never been done before.

In this book, Dr. Soofastaei and his colleagues reveal how all mining managers can effectively deploy advanced analytics in their day-to-day operations- one business decision at a time. Most mining companies have a massive amount of data at their disposal. However, they cannot use the stored data in any meaningful way. The powerful new business tool-advanced analytics enables many mining companies to aggressively leverage their data in key business decisions and processes with impressive results. From statistical analysis to machine learning and artificial intelligence, the authors show how many analytical tools can improve decisions about everything in the mine value chain, from exploration to marketing. Combining the science of advanced analytics with the mining industrial business solutions, introduce the "Advanced Analytics in Mining Engineering Book" as a practical road map and tools for unleashing the potential buried in your company's data. The book is aimed at providing mining executives, managers, and research and development teams with an understanding of the business value and applicability of different analytic approaches and helping data analytics leads by giving them a business framework in which to assess the value, cost, and risk of potential analytical solutions. In addition, the book will provide the next generation of miners - undergraduate and graduate IT and mining engineering students - with an understanding of data analytics applied to the mining industry. By providing a book with chapters structured in line with the mining value chain, we will provide a clear, enterprise-level view of where and how advanced data analytics can best be applied. This book highlights the potential to interconnect activities in the mining enterprise better. Furthermore, the book explores the opportunities for optimization and increased productivity offered by better interoperability along the mining value chain - in line with the emerging vision of creating a digital mine with much-enhanced capabilities for modeling, simulation, and the use of digital twins - in line with leading "digital" industries.

Over the last two decades, the field of public administration has witnessed theoretical and practical changes that have innovated the relationships between public administration and performance management. Dealing with the rising complexity of performance regimes in contemporary public administration requires that policy-makers and their organizations are able to face unpredictable problems impacting on a community's quality of life. Complex policy issues - such as immigration, pandemics, societal aging, crime, unemployment, and financial crises - cannot be easily solved by quick fixes that are focused only on a short-term and bounded vision of their causes. They rather require "robust" methods to support policy analysis and to affect sustainable community outcomes in cross-boundary settings. As illustrated in this book, Dynamic Performance Management provides a methodological framework enabling policy-makers to outline the causal relationships among policy outcomes, performance drivers, and related strategic resources. Such a modeling approach helps stakeholders to broaden the investigated system boundaries so to balance short- and long-term performance under different result domains. This approach blends performance management and System Dynamics modeling. Several examples and case studies are discussed to enable scholars and practitioners to appreciate the practical implications related to the use of such an approach.

This book provides students and researchers with a resource that includes the current application of the multi-criteria decision theory in a variety of fields, including the environment, health care, engineering, and architecture. There are many critical parameters (criteria) that can directly or indirectly affect the consequences of various decisions. The application of the multi-criteria decision theory focusses mainly on the use of computational methods which include multiple criteria and orders of preference for the evaluation and the selection of the best option among many alternatives based on the desired outcome. The theory of multi-criteria decision making (MCDM) is an approach that can be extremely useful for students, managers, engineers of manufacturing companies, etc.

Covid-19 has hit the world unprepared, as the deadliest pandemic of the century. Governments and authorities, as leaders and decision makers fighting against the virus, enormously tap on the power of AI and its data analytics models for urgent decision supports at the greatest efforts, ever seen from human history. This book showcases a collection of important data analytics models that were used during the epidemic, and discusses and compares their efficacy and limitations. Readers who from both healthcare industries and academia can gain unique insights on how data analytics models were designed and applied on epidemic data. Taking Covid-19 as a case study, readers especially those who are working in similar fields, would be better prepared in case a new wave of virus epidemic may arise again in the near future.

Earned Value Management (EVM) is a project management technique for measuring project progress in terms of cost, schedule and scope, and has developed into a very effective way to uncover performance problems at an early and correctible stage in any given project. From its earliest days as a financial analysis tool in the US in the early 1960 s, it steadily grew in use through the US Department of Defense until it was made the standard measurement for all DoD, NASA, and Department of Energy projects, and was widely adopted by publicly-traded companies trying to comply with the 2002 Sarbanes-Oxley ruling calling for greater transparency and accountability. It has also long been used in software engineering projects.

Winning the 2008 Research Award from IPMA for his research leading to this proposed book, author Mario Vanhoucke has surveyed the published literature to find and evaluate the effectiveness of the latest developments (and established practices) in EVM. After first explaining the fundamentals and terminology of the practice, he explores all the latest research trends and then tests them against a group of fictitious projects to gauge their effectiveness, offering general results applicable to a wide set of project types that researchers and practitioners can use to expand their work in EVM-managed projects. With a focus on the simple calculations behind EVM systems, Vanhoucke shows how they can often lead to misinterpretation and frustration and how to avoid common mistakes.

Meant to complement rather than compete with the existing books on the subject, the proposed book deals with the project performance and control phases of the project life cycle to present a detailed investigation of the project s time performance measurement methods and risk analysis techniques in order to evaluate existing and newly developed methods in terms of their abilities to improve the corrective actions decision-making process during project tracking. As readers apply what is learned from the book, EVM practices will become even more effective in project management and cost engineering. Individual chapters look at simulation studies in forecast accuracy (under nine different scenarios); schedule adherence; time sensitivity; activity sensitivity; and using top-down or bottom-up project tracking. Vanhoucke also offers an actual real-life case study, a tutorial on the use of ProTrack software (newly developed based on his research) in EVM, and conclusions on the relative effectiveness for each technique presented. This will be an important read for anyone researching, using, or studying EVM and will certainly help to push the field forward in the coming years.

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This book focuses on the tactical planning level for spare parts management. It describes a series of multi-item inventory models and presents exact and heuristic optimization methods, including greedy heuristics that work well for real, life-sized problems. The intended audience consists of graduate students, starting scholars in the field of spare parts inventory control, and spare parts planning specialists in the industry. In individual chapters the authors consider topics including: a basic single-location model; single-location models with multiple machine types and/or machine groups; the multi-location model with lateral transshipments; the classical METRIC model and its generalization to multi-indenture systems; and a single-location model with an explicit modeling of the repair capacity for failed parts and the priorities that one can set there. Various chapters of the book are used in a master course at Eindhoven University of Technology and in a PhD course of the Graduate Program Operations Management and Logistics (a Dutch network that organizes PhD courses in the field of OM&L). The required pre-knowledge consists of probability theory and basic knowledge of Markov processes and queuing theory. End-of-chapter problems appear for all chapters, with some answers appearing in an appendix.

This fifth edition of "Product Lifecycle Management" updates and adds to the successful fourth edition, the most frequently cited PLM publication. It gives the reader a thorough explanation of Product Lifecycle Management (PLM) and provides them with a full understanding and the skills to implement PLM within their own business environment. This new and expanded edition is fully updated to reflect the many technological and management advances made in PLM since the release of the fourth edition. "Product Lifecycle Management" will broaden the reader's understanding of PLM, nurturing the skills needed to implement PLM successfully and to achieve world-class product performance across the lifecycle. Among the components of PLM described are product-related business processes, product data, product data management (PDM) systems, other PLM applications, best practices, company objectives and organisation. This book also describes the relationships of PLM with the Internet of Things, Industry 4.0, Digital Twins and Digital Threads. "Product Lifecycle Management" (5th edition) explains what PLM is, and why it is needed. It describes the environment in which products are ideated, developed, manufactured, supported and retired, before addressing the main components of PLM and PLM Initiatives. Key activities in PLM Initiatives described include organisational change management (OCM) and project management. The final part of the book addresses the PLM Initiative, showing the typical steps and activities of a PLM project or initiative.

This graduate-level textbook covers modelling, programming and analysis of stochastic computer simulation experiments, including the mathematical and statistical foundations of simulation and why it works. The book is rigorous and complete, but concise and accessible, providing all necessary background material. Object-oriented programming of simulations is illustrated in Python, while the majority of the book is programming language independent. In addition to covering the foundations of simulation and simulation programming for applications, the text prepares readers to use simulation in their research. A solutions manual for end-of-chapter exercises is available for instructors.

This book covers important issues related to managing supply chain risks from various perspectives. Supply chains today are vulnerable to disruptions with a significant impact on firms' business and performance. The aim of supply chain risk management is to identify the potential sources of risks and implement appropriate actions in order to mitigate supply chain disruptions. This book presents a set of models, frameworks, strategies, and analyses that are essential for managing supply chain risks. As a comprehensive collection of the latest research and most recent cutting-edge developments on supply chain risk and its management, the book is structured into three main parts: 1) Supply Chain Risk Management; 2) Supply Chain Vulnerability and Disruptions Management; and 3) Toward a Resilient Supply Chain. Leading academic researchers as well as practitioners have contributed chapters, combining theoretical findings and research results with a practical and contemporary view on how companies can manage the supply chain risks and disruptions, as well as how to create a resilient supply chain. This book can serve as an essential source for students and scholars who are interested in pursuing research or teaching courses in the rapidly growing area of supply chain risk management. It can also provide an interesting and informative read for managers and practitioners who need to deepen their knowledge of effective supply chain risk management.

The analysis and design of engineering and industrial systems has come to rely heavily on the use of optimization techniques. The theory developed over the last 40 years, coupled with an increasing number of powerful computational procedures, has made it possible to routinely solve problems arising in such diverse fields as aircraft design, material flow, curve fitting, capital expansion, and oil refining just to name a few. Mathematical programming plays a central role in each of these areas and can be considered the primary tool for systems optimization. Limits have been placed on the types of problems that can be solved, though, by the difficulty of handling functions that are not everywhere differentiable. To deal with real applications, it is often necessary to be able to optimize functions that while continuous are not differentiable in the classical sense. As the title of the book indicates, our chief concern is with (i) nondifferentiable mathematical programs, and (ii) two-level optimization problems. In the first half of the book, we study basic theory for general smooth and nonsmooth functions of many variables. After providing some background, we extend traditional (differentiable) nonlinear programming to the nondifferentiable case. The term used for the resultant problem is nondifferentiable mathematical programming. The major focus is on the derivation of optimality conditions for general nondifferentiable nonlinear programs. We introduce the concept of the generalized gradient and derive Kuhn-Tucker-type optimality conditions for the corresponding formulations.

Franz Ferschl is seventy. According to his birth certificate it is true, but it is unbelievable. Two of the three editors remembers very well the Golden Age of Operations Research at Bonn when Franz Ferschl worked together with Wilhelm Krelle, Martin Beckmann and Horst Albach. The importance of this fruitful cooperation is reflected by the fact that half of the contributors to this book were strongly influenced by Franz Ferschl and his colleagues at the University of Bonn. Clearly, Franz Ferschl left his traces at all the other places of his professional activities, in Vienna and Munich. This is demonstrated by the present volume as well. Born in 1929 in the Upper-Austrian Miihlviertel, his scientific education brought him to Vienna where he studied mathematics. In his early years he was attracted by Statistics and Operations Research. During his employment at the Osterreichische Bundeskammer fUr Gewerbliche Wirtschaft in Vienna he prepared his famous book on queueing theory and stochastic processes in economics. This work has been achieved during his scarce time left by his duties at the Bundeskammer, mostly between 6 a.m. and midnight. All those troubles were, however, soon rewarded by the chair of statistics at Bonn University. As a real Austrian, the amenities of the Rhineland could not prevent him from returning to Vienna, where he took the chair of statistics.

Logistics and supply chain management is facing disruptive economic, technological and climate change developments that require new strategies. New technologies such as the Internet-of-Things, digital manufacturing or blockchain are emerging quickly and could provide competitive advantage to those companies that leverage the technologies smartly while managers that do not adopt and embrace change could be left behind. Last but perhaps most important for mankind, sustainability aspects such as low-carbon transportation, closed loop supply chains or socially-responsible supply chain setups will become essential to operate successfully in the future. All these aspects will affect logistics and supply chains as a whole as well as different functional areas such as air cargo, maritime logistics or sourcing/procurement. This book aims to dive into several of these functional topics to highlight the key developments in the next decade predicted by leading global experts in the field. It features contributions and key insights of globally leading scholars and senior industry experts. Their forward-looking perspectives on the anticipated trends are aimed at informing the reader about how logistics and supply chain management will evolve in the next decade and which academic qualities and skills will be required to succeed in the "new normal" environment that will be characterized by volatile and increasingly disrupted business eco-systems. Future scenarios are envisaged to provide both practitioners and students with insights that will help them to adapt and succeed in a fast changing world.

In the 21st century, advancements in the digital world are bringing about rapid waves of change in organizational management. As such, it is increasingly imperative to discover ways for businesses to adapt to changes in the markets and seize various digital marketing opportunities. Improving Business Performance Through Innovation in the Digital Economy is an essential reference source for the latest research on the impact of digital computing. It investigates new economic and entrepreneurial approaches to enhancing community development. Featuring research on topics such as business ethics, mobile technology, and cyber security, this book is ideally designed for knowledge workers, business managers, executives, entrepreneurs, small and medium enterprise managers, academicians, researchers, students, and global leaders seeking coverage on the management of sustainable enterprises.