Set-valued optimization is a vibrant and expanding branch of mathematics that deals with optimization problems where the objective map and/or the constraints maps are set-valued maps acting between certain spaces. Since set-valued maps subsumes single valued maps, set-valued optimization provides an important extension and unification of the scalar as well as the vector optimization problems. Therefore this relatively new discipline has justifiably attracted a great deal of attention in recent years. This book presents, in a unified framework, basic properties on ordering relations, solution concepts for set-valued optimization problems, a detailed description of convex set-valued maps, most recent developments in separation theorems, scalarization techniques, variational principles, tangent cones of first and higher order, sub-differential of set-valued maps, generalized derivatives of set-valued maps, sensitivity analysis, optimality conditions, duality and applications in economics among other things.

In this book methods from Operations Research and Game Theory are used to determine companies' profit-maximizing strategies related to pricing and (cooperative) advertising. It considers different supply chain structures as well as various distributions of power, making it possible to analyze both inter-echelon and intra-echelon dependencies between the companies' decisions. Additionally, an approach based on fuzzy set theory is presented in order to compensate for incomplete or missing data on market characteristics. Vertical cooperative advertising is an essential element of partnerships between manufacturers and retailers, allowing manufacturers to financially support their retailers' advertising efforts so as to increase sales for the entire supply chain. Given that such programs not only make up a considerable part of many companies' advertising budgets, but are also a controversial subject in many business relations, their correct design is of particular importance.

Systems Thinking for a Turbulent World will help practitioners in any field of change engage more effectively in transformative innovation. Such innovation addresses the paradigm shift needed to meet the diverse unfolding global challenges facing us today, often summed up as the Anthropocene. Fragmentation of local and global societies is escalating, and this is aggravating vicious cycles. To heal the rifts, we need to reintroduce the human element into our understandings - whether the context is civic or scientific - and strengthen truth-seeking in decision-making. Aided by appropriate concepts and methods, this healing will enable a switch from reaction to anticipation, even in the face of discontinuous change and high uncertainty. The outcome is to privilege the positive human skills for collaborative navigation through uncertainty over the disjointed rationality of mechanism and artificial intelligence, which increasingly alienates us. The reader in search of new ways of thinking will be introduced to concepts new to systems thinking that integrate systems thinking and futures thinking. The concept of anticipatory present moment (APM) serves as a basis for learning the cognitive skills that better enable navigation through turbulent times. A key personal and team practice is participative repatterning, which is the basis for transformative innovation. This practice is aided by new methods of visual facilitation. The reader is guided through the unfolding of the ideas and practices with a narrative based on the metaphor of search portrayed in the tradition of ox herding, found in traditional Far Eastern consciousness practice.

This book provides a perspective on a number of approaches to financial modelling and risk management. It examines both theoretical and practical issues. Theoretically, financial risks models are models of a real and a financial "uncertainty", based on both common and private information and economic theories defining the rules that financial markets comply to. Financial models are thus challenged by their definitions and by a changing financial system fueled by globalization, technology growth, complexity, regulation and the many factors that contribute to rendering financial processes to be continuously questioned and re-assessed. The underlying mathematical foundations of financial risks models provide future guidelines for risk modeling. The book's chapters provide selective insights and developments that can contribute to better understand the complexity of financial modelling and its ability to bridge financial theories and their practice. Future Perspectives in Risk Models and Finance begins with an extensive outline by Alain Bensoussan et al. of GLM estimation techniques combined with proofs of fundamental results. Applications to static and dynamic models provide a unified approach to the estimation of nonlinear risk models. A second section is concerned with the definition of risks and their management. In particular, Guegan and Hassani review a number of risk models definition emphasizing the importance of bi-modal distributions for financial regulation. An additional chapter provides a review of stress testing and their implications. Nassim Taleb and Sandis provide an anti-fragility approach based on "skin in the game". To conclude, Raphael Douady discusses the noncyclical CAR (Capital Adequacy Rule) and their effects of aversion of systemic risks. A third section emphasizes analytic financial modelling approaches and techniques. Tapiero and Vallois provide an overview of mathematical systems and their use in financial modeling. These systems span the fundamental Arrow-Debreu framework underlying financial models of complete markets and subsequently, mathematical systems departing from this framework but yet generalizing their approach to dynamic financial models. Explicitly, models based on fractional calculus, on persistence (short memory) and on entropy-based non-extensiveness. Applications of these models are used to define a modeling approach to incomplete financial models and their potential use as a "measure of incompleteness". Subsequently Bianchi and Pianese provide an extensive overview of multi-fractional models and their important applications to Asset price modeling. Finally, Tapiero and Jinquyi consider the binomial pricing model by discussing the effects of memory on the pricing of asset prices.

This book is dedicated to the issues and complexities of industrial services supply chain management. It analyzes how the transition from products to services can be managed, and how supply chains can be adjusted to reflect this new status quo. The book begins with chapters examining product-service systems structures and servitization - the services infusion process. Next, it presents industrial services as marketing and operations strategy. The focus shifts to service delivery, and this chapter discusses how the actual operations take place. This is followed by an examination of the role of technology and how connected assets are utilized by product vendors in value-creation. The book analyzes the transition from ownership to subscriptions in the pricing decisions chapter. Then the value chain effects chapter offers an overview of the mechanisms through which industrial companies are shortening the distance to end-users and aim for a better position in the value chain. Finally the conclusion addresses theoretical and empirical implications in the industrial services supply chain management.

This book provides an overview of behavioral decision theory and related research findings. In brief, behavioral decision theory is a general term for descriptive theories to explain the psychological knowledge related to decision-making behavior. It is called a theory, but actually it is a combination of various psychological theories, for which no axiomatic systems, such as the utility theory widely used in economics, have been established; it is often limited to qualitative knowledge. However, as suggested in the studies of H. A. Simon, who won the Nobel Prize for Economics in 1978, and D. Kahneman, who won the prize in 2002, the psychological methodology and knowledge of behavioral decision theory have been applied widely in such fields as economics, business administration, and engineering, and are expected to become more useful in the future. This book explains various behavioral decision theories related to decision-making processes. Numerous models have been proposed to explain the psychological processes related to such a selection of decision strategies, and this book also introduces some new models that are useful to explain decision-making processes. The book concludes with speculation about the future of modern behavioral decision theories while referring to their relation to fields associated with neuroscience, such as neuroeconomics, that have been developed in recent years. In addition, each chapter includes a bibliography that can be referred to when studying more details related to behavioral decision theory. Reading this book requires no advanced expertise; nonetheless, an introductory knowledge of psychology, business administration, and economics, and approximately a high school graduate's level of mathematics should facilitate the reader's comprehension of the content.

This book reports on the development and validation of a generic defeasible logic programming framework for carrying out argumentative reasoning in Semantic Web applications (GF@SWA). The proposed methodology is unique in providing a solution for representing incomplete and/or contradictory information coming from different sources, and reasoning with it. GF@SWA is able to represent this type of information, perform argumentation-driven hybrid reasoning to resolve conflicts, and generate graphical representations of the integrated information, thus assisting decision makers in decision making processes. GF@SWA represents the first argumentative reasoning engine for carrying out automated reasoning in the Semantic Web context and is expected to have a significant impact on future business applications. The book provides the readers with a detailed and clear exposition of different argumentation-based reasoning techniques, and of their importance and use in Semantic Web applications. It addresses both academics and professionals, and will be of primary interest to researchers, students and practitioners in the area of Web-based intelligent decision support systems and their application in various domains.

Many interesting and important results on stochastic scheduling problems have been developed in recent years, with the aid of probability theory. This book provides a comprehensive and unified coverage of studies in stochastic scheduling. The objective is two-fold: (i) to summarize the elementary models and results in stochastic scheduling, so as to offer an entry-level reading material for students to learn and understand the fundamentals of this area and (ii) to include in details the latest developments and research topics on stochastic scheduling, so as to provide a useful reference for researchers and practitioners in this area. Optimal Stochastic Scheduling is organized into two parts: Chapters 1-4 cover fundamental models and results, whereas Chapters 5-10 elaborate on more advanced topics. More specifically, Chapter 1 provides the relevant basic theory of probability and then introduces the basic concepts and notation of stochastic scheduling. In Chapters 2 and 3, the authors review well-established models and scheduling policies, under regular and irregular performance measures, respectively. Chapter 4 describes models with stochastic machine breakdowns. Chapters 5 and 6 introduce, respectively, the optimal stopping problems and the multi-armed bandit processes, which are necessary for studies of more advanced subjects in subsequent chapters. Chapter 7 is focused on optimal dynamic policies, which allow adjustments of policies based on up-to-date information. Chapter 8 describes stochastic scheduling with incomplete information in the sense that the probability distributions of random variables contain unknown parameters, which can however be estimated progressively according to updated information. Chapter 9 is devoted to the situation where the processing time of a job depends on the time when it is started. Lastly, in Chapter 10 the authors look at several recent models beyond those surveyed in the previous chapters.

Scheduling theory has received a growing interest since its origins in the second half of the 20th century. Developed initially for the study of scheduling problems with a single objective, the theory has been recently extended to problems involving multiple criteria. However, this extension has still left a gap between the classical multi-criteria approaches and some real-life problems in which not all jobs contribute to the evaluation of each criterion. In this book, we close this gap by presenting and developing multi-agent scheduling models in which subsets of jobs sharing the same resources are evaluated by different criteria. Several scenarios are introduced, depending on the definition and the intersection structure of the job subsets. Complexity results, approximation schemes, heuristics and exact algorithms are discussed for single-machine and parallel-machine scheduling environments. Definitions and algorithms are illustrated with the help of examples and figures.

This volume contains two types of papers-a selection of contributions from the "Second International Conference in Network Analysis" held in Nizhny Novgorod on May 7-9, 2012, and papers submitted to an "open call for papers" reflecting the activities of LATNA at the Higher School for Economics. This volume contains many new results in modeling and powerful algorithmic solutions applied to problems in * vehicle routing * single machine scheduling * modern financial markets * cell formation in group technology * brain activities of left- and right-handers * speeding up algorithms for the maximum clique problem * analysis and applications of different measures in clustering The broad range of applications that can be described and analyzed by means of a network brings together researchers, practitioners, and other scientific communities from numerous fields such as Operations Research, Computer Science, Transportation, Energy, Social Sciences, and more. The contributions not only come from different fields, but also cover a broad range of topics relevant to the theory and practice of network analysis. Researchers, students, and engineers from various disciplines will benefit from the state-of-the-art in models, algorithms, technologies, and techniques presented.

The theory of path dependence continues to attract great interest in a range of disciplines. An increasing number of scholars have started to explicitly use this theory for studying organizational inertia and institutional rigidities. This volume presents a collection of papers from various international conferences that address these issues.

How can we advance knowledge? Which methods do we need in order to make new discoveries? How can we rationally evaluate, reconstruct and offer discoveries as a means of improving the 'method' of discovery itself? And how can we use findings about scientific discovery to boost funding policies, thus fostering a deeper impact of scientific discovery itself? The respective chapters in this book provide readers with answers to these questions. They focus on a set of issues that are essential to the development of types of reasoning for advancing knowledge, such as models for both revolutionary findings and paradigm shifts; ways of rationally addressing scientific disagreement, e.g. when a revolutionary discovery sparks considerable disagreement inside the scientific community; frameworks for both discovery and inference methods; and heuristics for economics and the social sciences.

Metaheuristics, and evolutionary algorithms in particular, are known to provide efficient, adaptable solutions for many real-world problems, but the often informal way in which they are defined and applied has led to misconceptions, and even successful applications are sometimes the outcome of trial and error. Ideally, theoretical studies should explain when and why metaheuristics work, but the challenge is huge: mathematical analysis requires significant effort even for simple scenarios and real-life problems are usually quite complex. In this book the editors establish a bridge between theory and practice, presenting principled methods that incorporate problem knowledge in evolutionary algorithms and other metaheuristics. The book consists of 11 chapters dealing with the following topics: theoretical results that show what is not possible, an assessment of unsuccessful lines of empirical research; methods for rigorously defining the appropriate scope of problems while acknowledging the compromise between the class of problems to which a search algorithm is applied and its overall expected performance; the top-down principled design of search algorithms, in particular showing that it is possible to design algorithms that are provably good for some rigorously defined classes; and, finally, principled practice, that is reasoned and systematic approaches to setting up experiments, metaheuristic adaptation to specific problems, and setting parameters. With contributions by some of the leading researchers in this domain, this book will be of significant value to scientists, practitioners, and graduate students in the areas of evolutionary computing, metaheuristics, and computational intelligence.

Profiles in Operations Research: Pioneers and Innovators recounts the development of the field of Operations Research (OR), the science of decision making. The book traces the development of OR from its military origins to a mature discipline that is recognized worldwide for its contributions to managerial planning and complex global operations. Over the past six decades, OR analyses have impacted our daily lives: when making an airline or hotel reservation, waiting in line at a bank, getting the correctly blended fuel at the gas station, and ensuring that the book you are holding arrived at its destination on time. OR originated in the late 1930s when British scientists from various disciplines joined Royal Air Force officers to determine the most effective way to employ new radar technology for intercepting enemy aircraft. During World War II, similar applied research groups were formed to study, test, and evaluate military operations on both sides of the Atlantic. Their work resulted in great improvements-OR helped the Allies win the war. The scientific field that emerged from these studies was called operational research in the U.K. and operations research in the U.S. Today, OR provides a broad and powerful science to aid decision making. Profiles describes the lives and contributions of 43 OR pioneers and innovators and relates how these individuals, with varying backgrounds and diverse interests, were drawn to the nascent field of OR. The profiles also describe how OR techniques and applications expanded considerably beyond the military context to find new domains in business and industry. In addition to their scientific contributions, these profiles capture the life stories of the individuals-interwoven with personal tales, vivid vignettes, family backgrounds, and views of the mission and future of OR. Collectively, the profiles recount the fascinating story of the growth and development of a field enriched by the convergence of different disciplines. The Editors: Arjang A. Assad is Dean of the School of Management, University at Buffalo, State University of New York. Saul I. Gass is Professor Emeritus, Department of Decision, Operations & Information Technologies, Smith School of Business, University of Maryland, College Park. From the Reviews Profiles In Operations Research: Pioneers and Innovators. Book Review by Nigel Cummings: U.K. OR Society's e-journal, Inside OR., Sept 2011. "I can thoroughly recommend this book. I found it both enlighteningand undeniably gripping, so much so in fact, you may find it difficultto put it down once you have commenced reading it. Arjang A. Assad and Saul I. Gass have created a masterwork whichwill serve to immortalise [stet] the pioneers of O.R. for many years to come." *For a list of all known typos, plus further discussion on the book, please visit http://profilesinoperationsresearch.com.

This volume contains a selection of contributions that were presented at the Modeling and Optimization: Theory and Applications Conference (MOPTA) held at Lehigh University in Bethlehem, Pennsylvania, USA on July 30-August 1, 2012. The conference brought together a diverse group of researchers and practitioners, working on both theoretical and practical aspects of continuous or discrete optimization. Topics presented included algorithms for solving convex, network, mixed-integer, nonlinear, and global optimization problems, and addressed the application of optimization techniques in finance, logistics, health, and other important fields. The contributions contained in this volume represent a sample of these topics and applications and illustrate the broad diversity of ideas discussed at the meeting.

This work is devoted to the late Ukrainian computer scientist V. M. Glushkov on the 90th anniversary of his birthday. Dr. Glushkov is known for his contribution to the world computer science and technology and this volume analyzes the ideas and paths of development of informatics formulated by him and demonstrate their important role in constructing computer technologies of basic research in the fields of applied mathematics, theories of computer programming and computing systems. A significant portion of the monograph is devoted to the elucidation of new results obtained in the field of mathematical modeling of complicated processes, creation of new methods for solving and investigating optimization problems in different statements and development of computer technologies for investigations in the field of economy, biology, medicine and information security in systems. The monograph will be of particular interest to informatics specialists and experts using methods of informatics and computer technologies to investigate complicated processes of different natures and developing new information technologies. It may also be useful for both graduate students and postgraduates specializing in Computer Science.

With this book, distinguished and notable contributors wish to honor Professor Charles S. Tapiero's scientific achievements. Although it covers only a few of the directions Professor Tapiero has taken in his work, it presents important modern developments in theory and in diverse applications, as studied by his colleagues and followers, further advancing the topics Tapiero has been investigating. The book is divided into three parts featuring original contributions covering the following areas: general modeling and analysis; applications to marketing, economy and finance; and applications to operations and manufacturing. Professor Tapiero is among the most active researchers in control theory; in the late sixties, he started to enthusiastically promote optimal control theory along with differential games, successfully applying it to diverse problems ranging from classical operations research models to finance, risk and insurance, marketing, transportation and operations management, conflict management and game theory, engineering, regional and urban sciences, environmental economics, and organizational behavior. Over the years, Professor Tapiero has produced over 300 papers and communications and 14 books, which have had a major impact on modern theoretical and applied research. Notable among his numerous pioneering scientific contributions are the use of graph theory in the behavioral sciences, the modeling of advertising as a random walk, the resolution of stochastic zero-sum differential games, the modeling of quality control as a stochastic competitive game, and the development of impulsive control methods in management. Charles Tapiero's creativity applies both in formulating original issues, modeling complex phenomena and solving complex mathematical problems.

This book integrates socially responsible investment into modern portfolio theory from a multi-criteria perspective. Socially responsible investment is a "new deal" championed by the institutional investment and bank sectors, agents that influence mutual funds and other collective investment schemes and which fear that financial strategies without ethical constraints can harm sustainable growth and prosperity. The book shows how to combine financial criteria such as profitability and risk with non-financial criteria such as the protection of the ecosystem, responsible consumption of energy, and healthcare campaigns. The book's first part presents critical issues in ethical investment, while the second explains in detail the application of goal programming techniques for SRI funds, illustrating their use in actual cases. Part three demonstrates how compromise programming can be applied in the contexts of portfolio selection and risk management. Finally, in its fourth part the book examines the application of other decision-making support methods like the Analytic Hierarchy Process (AHP) framework, the Reference Point Method, and soft computing techniques for portfolio selection.

Florian Brauner addresses the risk reduction effects of security measures (SecMe) as well as economic and social effects using terrorist threats in public transportation as use case. SecMe increase the level of security but cause interferences and restrictions for customers (e.g. privacy). This study identifies the interferences and analyzes the acceptance with an empirical survey of customers. A composite indicator for the acceptance of different SecMe is developed and integrated into a risk management framework for multi-criteria decision analysis achieving the right balance of risk reduction, costs, and social acceptance.

Putting forward a unified presentation of the features and possible applications of probabilistic preferences composition, and serving as a methodology for decisions employing multiple criteria, this book maximizes reader insights into the evaluation in probabilistic terms and the development of composition approaches that do not depend on assigning weights to the criteria. With key applications in important areas of management such as failure modes, effects analysis and productivity analysis - together with explanations about the application of the concepts involved -this book makes available numerical examples of probabilistic transformation development and probabilistic composition. Useful not only as a reference source for researchers, but also in teaching classes of graduate courses in Production Engineering and Management Science, the key themes of the book will be of especial interest to researchers in the field of Operational Research.

This book reports on cutting-edge research carried out within the context of the EU-funded Dicode project, which aims at facilitating and augmenting collaboration and decision making in data-intensive and cognitively complex settings. Whenever appropriate, Dicode builds on prominent high-performance computing paradigms and large data processing technologies to meaningfully search, analyze, and aggregate data from diverse, extremely large and rapidly evolving sources. The Dicode approach and services are fully explained and particular emphasis is placed on deepening insights regarding the exploitation of big data, as well as on collaboration and issues relating to sense-making support. Building on current advances, the solution developed in the Dicode project brings together the reasoning capabilities of both the machine and humans. It can be viewed as an innovative "workbench" incorporating and orchestrating a set of interoperable services that reduce the data intensiveness and complexity overload at critical decision points to a manageable level, thus permitting stakeholders to be more productive and effective in their work practices.

This book reports on cutting-edge research in innovative systems interfaces, with an emphasis on both lifecycle development and human-technology interaction, especially in the cases of virtual, augmented and mixed reality systems. It describes advanced methodologies and tools for evaluating and improving interface usability and covers new models, as well as case studies and good practices. The book reports on considerations of the human, hardware, and software factors in the process of developing interfaces for optimizing total system performance, especially innovative computing technologies for teams dealing with dynamic environments, while minimizing total ownership costs. One of the main purposes is to discuss forces currently shaping the nature of computing and systems including: the needs of decreasing hardware costs; the importance of portability, which translates to the modern tendency of hardware miniaturization and technologies for reducing power requirements; the necessity of a better assimilation of computation in the environment; and social concerns about access to computers and systems for people with special needs. The book, which is based on the AHFE 2016 International Conference on Human Factors and System Interactions, held on July 27-31, 2016, in Walt Disney World (R), Florida, USA, offers a timely survey and practice-oriented guide for systems interface users and developers alike.

As operations research (OR) applications continue to grow and flourish in a number of decision making fields, a reference that is comprehensive, concise, and easy to read is more than a nicety, it is a necessity. This book provides a single volume overview of OR applications in practice, making it the first resource a practitioner would reach for when faced with an OR problem or application. Written by leading authorities in the field, the book covers functional and industry specific areas of OR applications. Ideally suited for practitioners in business, industry, and government, the book can also be used as a supplemental text in undergraduate or graduate OR courses.

This book explores economic concepts related to disaster losses, describes mechanisms that determine the economic consequences of a disaster, and reviews methodologies for making decisions regarding risk management and adaptation. The author addresses the need for better understanding of the consequences of disasters and reviews and analyzes three scientific debates on linkage between disaster risk management and adaptation to climate change. The first involves the existence and magnitude of long-term economic impact of natural disasters on development. The second is the disagreement over whether any development is the proper solution to high vulnerability to disaster risk. The third debate involves the difficulty of drawing connections between natural disasters and climate change and the challenge in managing them through an integrated strategy. The introduction describes economic views of disaster, including direct and indirect costs, output and welfare losses, and use of econometric tools to measure losses. The next section defines disaster risk, delineates between "good" and "bad" risk-taking, and discusses a pathway to balanced growth. A section entitled "Trends in Hazards and the Role of Climate Change" sets scenarios for climate change analysis, discusses statistical and physical models for downscaling global climate scenarios to extreme event scenarios, and considers how to consider extremes of hot and cold, storms, wind, drought and flood. Another section analyzes case studies on hurricanes and the US coastline; sea-level rises and storm surge in Copenhagen; and heavy precipitation in Mumbai. A section on Methodologies for disaster risk management includes a study on cost-benefit analysis of coastal protections in New Orleans, and one on early-warning systems in developing countries. The next section outlines decision-making in disaster risk management, including robust decision-making, No-regret and No-risk strategies; and strategies that reduce time horizons for decision-making. Among the conclusions is the assertion that risk management policies must recognize the benefits of risk-taking and avoid suppressing it entirely. The main message is that a combination of disaster-risk-reduction, resilience-building and adaptation policies can yield large potential gains and synergies.

This book explores how enterprises adapt to challenges in their business environments. It focuses on the critical elements within organisations that every executive must address in order to remain competitive. It takes a pluralist approach in trying to broaden our knowledge on organisational adaptations. It also offers an exploratory delve into existing literature of organisational study. This is biased for content, context and process framework and processual analytic approach in order to identify, determine, understand the intricacies of adaptations going on in various business organisations. The book also includes a case study of how Kodak and Fujifilm responded to digitalisation of photographic film industry, which is an example of major adaptation change. Many global brands are often contending with similar issues and real life challenges. Simply put, today's business environment demands a new way of doing business that challenges brand's existing core business philosophy. Organisations are 'individual' entities in their own rights. Businesses have devised ways of surviving their environments. They do this by downsizing, merger and acquisition, business ecosystems, other forms of collaborations and strategic alliances. While this is true, current research works into generic predictors and/or concepts that enhance the transformation process are scarce. It is particularly important to align the theories and concepts of organisational adaptations with realities in the business environment. This book delves deep and explains adaptations in organisations, but also offers insight for how executives can adapt and thrive in their dynamic business environments.