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.

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.

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.

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.

"

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.

'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 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.

This monograph presents a comprehensive treatment of the maximum-entropy sampling problem (MESP), which is a fascinating topic at the intersection of mathematical optimization and data science. The text situates MESP in information theory, as the algorithmic problem of calculating a sub-vector of pre-specificed size from a multivariate Gaussian random vector, so as to maximize Shannon's differential entropy. The text collects and expands on state-of-the-art algorithms for MESP, and addresses its application in the field of environmental monitoring. While MESP is a central optimization problem in the theory of statistical designs (particularly in the area of spatial monitoring), this book largely focuses on the unique challenges of its algorithmic side. From the perspective of mathematical-optimization methodology, MESP is rather unique (a 0/1 nonlinear program having a nonseparable objective function), and the algorithmic techniques employed are highly non-standard. In particular, successful techniques come from several disparate areas within the field of mathematical optimization; for example: convex optimization and duality, semidefinite programming, Lagrangian relaxation, dynamic programming, approximation algorithms, 0/1 optimization (e.g., branch-and-bound), extended formulation, and many aspects of matrix theory. The book is mainly aimed at graduate students and researchers in mathematical optimization and data analytics.

One of the most well-known of all network optimization problems is the shortest path problem, where a shortest connection between two locations in a road network is to be found. This problem is the basis of route planners in vehicles and on the Internet. Networks are very common structures; they consist primarily of a ?nite number of locations (points, nodes), together with a number of links (edges, arcs, connections) between the locations. Very often a certain number is attached to the links, expressing the distance or the cost between the end points of that connection. Networks occur in an extremely wide range of applications, among them are: road networks; cable networks; human relations networks; project scheduling networks; production networks; distribution networks; neural networks; networks of atoms in molecules. In all these cases there are "objects" and "relations" between the objects. A n- work optimization problem is actually nothing else than the problem of ?nding a subset of the objects and the relations, such that a certain optimization objective is satis?ed.

This book presents a consistent methodology for making decisions under uncertain conditions, as is almost always the case. Tools such as value of information and value of flexibility are explored as a means to make more complex and nuanced decisions. The book develops the complete formalism for assessing the value of acquiring information with two novel approaches. Firstly, it integrates the fuzzy characteristics of data, and secondly develops a methodology for assessing data acquisition actions that optimize the value of projects from a holistic perspective. The book also discusses the formalism for including flexibility in the project decision assessment. Practical examples of oil- and gas-related decision problems are included and discussed to facilitate the learning process. This book provides valuable advice and case studies applicable to engineers, researchers, and graduate students, particularly in the oil and gas industry and pharmaceutic industry.

Operations Research Management Science approaches have helped people for the last 40 years to understand the complex functioning of the systems based upon natural resources, as well as to manage natural resources in the most efficient manner. The areas usually viewed within the natural resources field are: agriculture, fisheries, forestry, and mining and water resources. All of these areas share the common problem of optimally allocating scarcity over a period of time. The scale of time or length of the planning horizon differs from one area to another. We have almost a continuous renewal in the case of the fisheries, periodic cycles in the case of agriculture and forestry and enormous periods of time much beyond the human perception in the case of mining resources. But in all the cases, the critical issue is to obtain an efficient use of the resource along its planned time horizon.

Another element of connection among the different natural resources is due to the interaction between the use of the resource and the environmental impact caused by its extraction or harvest. This type of interaction implies additional complexities in the underlying decision-making process, making the use of OR/MS tools especially relevant.

HANDBOOK OF OPERATIONS RESEARCH IN NATURAL RESOURCES will be the first systematic handbook treatment of quantitative modeling natural resource problems, their allocated efficient use, and societal and economic impact. AndrA(c)s Weintraub is the very top person in Natural Resource research. Moreover, he has an international reputation in OR and a former president of the International Federation of Operational Research Societies (IFORS). He has selectedco-editors who are at the top of the sub-fields in natural resources: agriculture, fisheries, forestry, and mining. The book will cover these areas in terms with contributions from researchers on modeling natural research problems, quantifying data, developing algorithms, and discussing the benefits of research implementations. The handbook will include tutorial contributions when necessary. Throughout the book, technological advances and algorithmic developments that have been driven by natural resource problems will be called out and discussed.

This book aims at providing cases with inspiring findings for global researchers in capacity allocation and reservation. Capacity allocation mechanisms are introduced in the book, as well as the measures to build models and the ways to achieve supply chain coordination. In addition, it illustrates the capacity reservation contract and quantity flexible contract with comparisons and some numerical studies. The book is divided into 7 chapters. Chapter 1 introduces the background and the latest development of the research. Chapter 2 introduces how to manage downstream competition through capacity allocation in symmetric market, including proportional mechanism and lexicographic mechanism. Demand competition is introduced in Chapter 3 as well as the uniform allocation mechanism and the comparisons among three different mechanisms. In Chapter 4, we give information about demand competition with fixed factor allocation, and the comparison with other allocations. Chapter 5 provides the optimal strategies under fixed allocation with multiple retailers and the impacts of fixed proportions. Chapter 6 illustrates how to achieve supply chain coordination through capacity reservation contract and its comparison with the quantity flexibility contract, and in Chapter 7 we describe outsourcing decisions and order policies in different systems with some numerical studies. We sincerely hope that this book can provide some useful suggestions and inspirations for scholars around the world who have the same interests in this field.

Using numerical examples to illustrate their concepts and results, this book examines recently developed fuzzy multi-criteria methods, such as Intuitionistic Fuzzy TOPSIS, Intuitionistic Fuzzy TOPSIS & DEA-AHP, Intuitionistic VIKOR, Pythagorean WASPAS, Pythagorean ENTROPI, Hesitant CBD, Hesitant MABAC, Triangular EDAS, Triangular PROMETHEE, q-Rung Orthopair COPRAS, and Fuzzy Type - 2 ELECTRE. Each chapter covers practical applications in addition to fresh developments and results. Given its structure and scope, the book can be used as a textbook in graduate courses on operations research and industrial engineering. It also offers a valuable resource for scientists working in a range of disciplines that require multi-criteria decision making.