The financial market melt-down of the years 2007-2009 has posed great challenges for studies on financial economics. This financial economics text focuses on the dynamic interaction of financial markets and economic activity. The financial market to be studied here encompasses the money and bond market, credit market, stock market and foreign exchange market; economic activity includes the actions and interactions of firms, banks, households, governments and countries. The book shows how economic activity affects asset prices and the financial market, and how asset prices and financial market volatility and crises impact economic activity. The book offers extensive coverage of new and advanced topics in financial economics such as the term structure of interest rates, credit derivatives and credit risk, domestic and international portfolio theory, multi-agent and evolutionary approaches, capital asset pricing beyond consumption-based models, and dynamic portfolio decisions. Moreover a completely new section of the book is dedicated to the recent financial market meltdown of the years 2007-2009. Emphasis is placed on empirical evidence relating to episodes of financial instability and financial crises in the U.S. and in Latin American, Asian and Euro-area countries. Overall, the book explains what researchers and practitioners in the financial sector need to know about the financial-real interaction, and what practitioners and policy makers need to know about the financial market.

The Prisoner's Dilemma is one of the most fiercely debated thought experiments in philosophy and the social sciences, presenting the simple insight that when two or more agents interact, the actions that most benefit each individual may not benefit the group. The fact that when you do what is best for you, and I do what is best for me, we end up in a situation that is worse for both of us makes the Prisoner's Dilemma relevant to a broad range of everyday phenomena. This volume of new essays from leading philosophers, game theorists, and economists examines the ramifications of the Prisoner's Dilemma, the directions in which it continues to lead us, and its links to a variety of topics in philosophy, political science, social science, economics, and evolutionary biology. The volume will be a vital and accessible resource for upper-level students as well as for academic researchers.

While mathematically sophisticated methods can be used to better understand and improve processes, the nonlinear nature of food processing models can make their dynamic optimization a daunting task. With contributions from a virtual who s who in the food processing industry, Optimization in Food Engineering evaluates the potential uses and limitations of optimization techniques for food processing, including classical methods, artificial intelligence-genetic algorithms, multi-objective optimization procedures, and computational fluid dynamics.

The book begins by delineating the fundamentals and methods for analytical and numerical procedures. It then covers optimization techniques and how they specifically apply to food processing. The final section digs deep into fundamental food processes and provides detailed explanation and examples from the most experienced and published authors in the field. This includes a range of processes from optimization strategies for improving the performance of batch reactors to the optimization of conventional thermal processing, microwave heating, freeze drying, spray drying, and refrigeration systems, to structural optimization techniques for developing beverage containers, optimization approaches for impingement processing, and optimal operational planning methodologies. Each chapter presents the required parameters for the given process with the optimization procedure to apply.

An increasing part of the food processor s job is to optimize systems to squeeze more dollars out of overhead to offset rising utility and transportation costs. Logically combining optimization techniques from many sources into a single volume focused on food production processes, this book provides real solutions to increases in energy, healthcare, and product liability costs that impact the bottom line in food production.

Das im heutigen Berufsalltag so wichtige und allgegenwartige "treffsichere Umgehen" mit mathematischen Methoden und Modellen setzt voraus, dass Studierende die relevanten Werkzeuge kennen und verstehen, sie auswahlen und anwenden sowie erzielte Ergebnis (auf Plausibilitat) prufen, bewerten und je nach Bedarf auf andere Fragestellungen transferieren bzw. zum Problemloesen einsetzen koennen. Ausgehend von der Schulmathematik vermitteln die Autoren dem Leser diese berufsrelevanten Fertigkeiten didaktisch hervorragend und gut zuganglich. Dabei ist jedes Kapitel neben vielen Aufgaben mit Loesungen mit einem Eingangs- und einem Ausgangstest versehen, um eine effiziente Lernkontrolle zu ermoeglichen.

Many of today's most commercially successful videogames, from Call of Duty to Company of Heroes, are war-themed titles that play out in what are framed as authentic real-world settings inspired by recent news headlines or drawn from history. While such games are marketed as authentic representations of war, they often provide a selective form of realism that eschews problematic, yet salient aspects of war. In addition, changes in the way Western states wage and frame actual wars makes contemporary conflicts increasingly resemble videogames when perceived from the vantage point of Western audiences. This interdisciplinary volume brings together scholars from games studies, media and cultural studies, politics and international relations, and related fields to examine the complex relationships between military-themed videogames and real-world conflict, and to consider how videogames might deal with history, memory, and conflict in alternative ways. It asks: What is the role of videogames in the formation and negotiation of cultural memory of past wars? How do game narratives and designs position the gaming subject in relation to history, war and militarism? And how far do critical, anti-war/peace games offer an alternative or challenge to mainstream commercial titles?

This textbook approaches optimization from a multi-aspect, multi-criteria perspective. By using a Multiple Criteria Decision Making (MCDM) approach, it avoids the limits and oversimplifications that can come with optimization models with one criterion. The book is presented in a concise form, addressing how to solve decision problems in sequences of intelligence, modelling, choice and review phases, often iterated, to identify the most preferred decision variant. The approach taken is human-centric, with the user taking the final decision is a sole and sovereign actor in the decision making process. To ensure generality, no assumption about the Decision Maker preferences or behavior is made. The presentation of these concepts is illustrated by numerous examples, figures, and problems to be solved with the help of downloadable spreadsheets. This electronic companion contains models of problems to be solved built in Excel spreadsheet files. Optimization models are too often oversimplifications of decision problems met in practice. For instance, modeling company performance by an optimization model in which the criterion function is short-term profit to be maximized, does not fully reflect the essence of business management. The company's managing staff is accountable not only for operational decisions, but also for actions which shall result in the company ability to generate a decent profit in the future. This calls for management decisions and actions which ensure short-term profitability, but also maintaining long-term relations with clients, introducing innovative products, financing long-term investments, etc. Each of those additional, though indispensable actions and their effects can be modeled separately, case by case, by an optimization model with a criterion function adequately selected. However, in each case the same set of constraints represents the range of company admissible actions. The aim and the scope of this textbook is to present methodologies and methods enabling modeling of such actions jointly.

Customer-Oriented Optimization in Public Transportation develops models, results and algorithms for optimizing public transportation from a customer-oriented point of view. The methods used are based on graph-theoretic approaches and integer programming. The specific topics are all motivated by real-world examples which occurred in practical projects. An appendix summarizes some of the basics of optimization needed to interpret the material in the book. In detail, the topics the book covers in its three parts are as follows: Stop location - Does it make sense to open new stations along existing bus or railway lines? If yes, in which locations? The problem is modeled as a continuous covering problem. To solve it, the author develops a finite dominating set and shows that efficient methods are possible if the special structure of the covering matrix is used; Delay management - Should a train wait for delayed feeder trains or should it depart in time?

Before the appearance of broadband links and wireless systems, networks have been used to connect people in new ways. Now, the modern world is connected through large-scale, computational networked systems such as the Internet. Because of the ever-advancing technology of networking, efficient algorithms have become increasingly necessary to solve some of the problems developing in this area.

"Mathematical Aspects of Network Routing Optimization" focuses on computational issues arisingfrom the process of optimizing network routes, such as quality of the resulting links and their reliability. Algorithms are a cornerstone for the understanding of the protocols underlying multicast routing. The main objectivein the text is to deriveefficient algorithms, with or without guarantee of approximation. Notes have been provided for basic topics such as graph theory and linear programming to assist those who are not fully acquainted with the mathematical topics presented throughout the book.

"Mathematical Aspects of Network Routing Optimization" provides a thorough introduction to the subject of algorithms for network routing, and focuses especially on multicast and wireless ad hoc systems. This book is designed for graduate students, researchers, and professionals interested in understanding the algorithmic and mathematical ideas behind routing in computer networks. It is suitable for advanced undergraduate students, graduate students, and researchers in the area of network algorithms."

This book presents the latest researches on hypersonic steady glide dynamics and guidance, including the concept of steady glide reentry trajectory and the stability of its regular perturbation solutions, trajectory damping control technique for hypersonic glide reentry, singular perturbation guidance of hypersonic glide reentry, trajectory optimization based on steady glide, linear pseudospectral generalized nominal effort miss distance guidance, analytical entry guidance and trajectory-shaping guidance with final speed and load factor constraints. They can be used to solve many new difficult problems in entry guidance. And many practical engineering cases are provided for the readers for better understanding. Researchers and students in the fields of flight vehicle design or flight dynamics, guidance and control could use the book as valuable reference.

This research monograph summarizes a line of research that maps certain classical problems of discrete mathematics and operations research - such as the Hamiltonian Cycle and the Travelling Salesman Problems - into convex domains where continuum analysis can be carried out. Arguably, the inherent difficulty of these, now classical, problems stems precisely from the discrete nature of domains in which these problems are posed. The convexification of domains underpinning these results is achieved by assigning probabilistic interpretation to key elements of the original deterministic problems. In particular, the approaches summarized here build on a technique that embeds Hamiltonian Cycle and Travelling Salesman Problems in a structured singularly perturbed Markov decision process. The unifying idea is to interpret subgraphs traced out by deterministic policies (including Hamiltonian cycles, if any) as extreme points of a convex polyhedron in a space filled with randomized policies. The above innovative approach has now evolved to the point where there are many, both theoretical and algorithmic, results that exploit the nexus between graph theoretic structures and both probabilistic and algebraic entities of related Markov chains. The latter include moments of first return times, limiting frequencies of visits to nodes, or the spectra of certain matrices traditionally associated with the analysis of Markov chains. However, these results and algorithms are dispersed over many research papers appearing in journals catering to disparate audiences. As a result, the published manuscripts are often written in a very terse manner and use disparate notation, thereby making it difficult for new researchers to make use of the many reported advances. Hence the main purpose of this book is to present a concise and yet easily accessible synthesis of the majority of the theoretical and algorithmic results obtained so far. In addition, the book discusses numerous open questions and problems that arise from this body of work and which are yet to be fully solved. The approach casts the Hamiltonian Cycle Problem in a mathematical framework that permits analytical concepts and techniques, not used hitherto in this context, to be brought to bear to further clarify both the underlying difficulty of NP-completeness of this problem and the relative exceptionality of truly difficult instances. Finally, the material is arranged in such a manner that the introductory chapters require very little mathematical background and discuss instances of graphs with interesting structures that motivated a lot of the research in this topic. More difficult results are introduced later and are illustrated with numerous examples.

Effective decision-making while trading off the constraints and conflicting multiple objectives under rapid technological developments, massive generation of data, and extreme volatility is of paramount importance to organizations to win over the time-based competition today. While agility is a crucial issue, the firms have been increasingly relying on evidence-based decision-making through intelligent decision support systems driven by computational intelligence and automation to achieve a competitive advantage.  The decisions are no longer confined to a specific functional area. Instead, business organizations today find actionable insight for formulating future courses of action by integrating multiple objectives and perspectives. Therefore, multi-objective decision-making plays a critical role in businesses and industries. In this regard, the importance of Operations Research (OR) models and their applications enables the firms to derive optimum solutions subject to various constraints and/or objectives while considering multiple functional areas of the organizations together. Hence, researchers and practitioners have extensively applied OR models to solve various organizational issues related to manufacturing, service, supply chain and logistics management, human resource management, finance, and market analysis, among others. Further, OR models driven by AI have been enabled to provide intelligent decision-support frameworks for achieving sustainable development goals. The present issue provides a unique platform to showcase the contributions of the leading international experts on production systems and business from academia, industry, and government to discuss the issues in intelligent manufacturing, operations management, financial management, supply chain management, and Industry 4.0 in the Artificial Intelligence era. Some of the general (but not specific) scopes of this proceeding entail OR models such as Optimization and Control, Combinatorial Optimization, Queuing Theory, Resource Allocation Models, Linear and Nonlinear Programming Models, Multi-objective and multi-attribute Decision Models, Statistical Quality Control along with AI, Bayesian Data Analysis, Machine Learning and Econometrics and their applications vis-à-vis AI & Data-driven Production Management, Marketing and Retail Management, Financial Management, Human Resource Management, Operations Management, Smart Manufacturing & Industry 4.0, Supply Chain and Logistics Management, Digital Supply Network, Healthcare Administration, Inventory Management, consumer behavior, security analysis, and portfolio management and sustainability.   The present issue shall be of interest to the faculty members, students, and scholars of various engineering and social science institutions and universities, along with the practitioners and policymakers of different industries and organizations.

The present volume is a collective monograph devoted to applications of the optimal design theory in optimization and statistics. The chapters re?ect the topics discussed at the workshop "W-Optimum Design and Related Statistical Issues" that took place in Juan-les-Pins, France, in May 2005. The title of the workshop was chosen as a light-hearted celebration of the work of Henry Wynn. It was supported by the Laboratoire I3S (CNRS/Universit e de Nice, Sophia Antipolis), to which Henry is a frequent visitor. The topics covered partly re?ect the wide spectrum of Henry's research - terests. Algorithms for constructing optimal designs are discussed in Chap. 1, where Henry's contribution to the ?eld is acknowledged. Steepest-ascent - gorithms used to construct optimal designs are very much related to general gradientalgorithmsforconvexoptimization. Inthelasttenyears, asigni?cant part of Henry's research was devoted to the study of the asymptotic prop- ties of such algorithms. This topic is covered by Chaps. 2 and 3. The work by Alessandra Giovagnoli concentrates on the use of majorization and stoch- tic ordering, and Chap. 4 is a hopeful renewal of their collaboration. One of Henry's major recent interests is what is now called algebraic statistics, the application of computational commutative algebra to statistics, and he was partly responsible for introducing the experimental design sub-area, reviewed in Chap. 5. One other sub-area is the application to Bayesian networks and Chap. 6 covers this, with Chap. 7 being strongly related."

This book analyzes the following four distinct, although not dissimilar, areas of social choice theory and welfare economics: nonstrategic choice, Harsanyi's aggregation theorems, distributional ethics and strategic choice. While for aggregation of individual ranking of social states, whether the persons behave strategically or non-strategically, the decision making takes place under complete certainty; in the Harsanyi framework uncertainty has a significant role in the decision making process. Another ingenious characteristic of the book is the discussion of ethical approaches to evaluation of inequality arising from unequal distributions of achievements in the different dimensions of human well-being. Given its wide coverage, combined with newly added materials, end-chapter problems and bibliographical notes, the book will be helpful material for students and researchers interested in this frontline area research. Its lucid exposition, along with non-technical and graphical illustration of the concepts, use of numerical examples, makes the book a useful text.

Optimization on Riemannian manifolds-the result of smooth geometry and optimization merging into one elegant modern framework-spans many areas of science and engineering, including machine learning, computer vision, signal processing, dynamical systems and scientific computing. This text introduces the differential geometry and Riemannian geometry concepts that will help applied mathematics, computer science and engineering students and researchers gain a firm mathematical grounding to use these tools confidently in their research. Its chart-last approach will prove more intuitive from an optimizer's viewpoint, and all definitions and theorems are motivated to build time-tested optimization algorithms. Starting from first principles, the text goes on to cover current research on topics including worst-case complexity and geodesic convexity. Readers will appreciate the tricks of the trade for conducting research and for numerical implementations sprinkled throughout the book.

ELEMENTARY LINEAR ALGEBRA, 8E, INTERNATIONAL METRIC EDITION's clear, careful, and concise presentation of material helps you fully understand how mathematics works. The author balances theory with examples, applications, and geometric intuition for a complete, step-by-step learning system. To engage you in the material, a new design highlights the relevance of the mathematics and makes the book easier to read. Data and applications reflect current statistics and examples, demonstrating the link between theory and practice. The companion website LarsonLinearAlgebra.com offers free access to multiple study tools and resources. CalcChat.com offers free step-by-step solutions to the odd-numbered exercises in the text.

In the quarter of a century since three mathematicians and game theorists collaborated to create Winning Ways for Your Mathematical Plays, the book has become the definitive work on the subject of mathematical games. Now carefully revised and broken down into four volumes to accommodate new developments, the Second Edition retains the original's wealth of wit and wisdom. The authors' insightful strategies, blended with their witty and irreverent style, make reading a profitable pleasure. In Volume 2, the authors have a Change of Heart, bending the rules established in Volume 1 to apply them to games such as Cut-cake and Loopy Hackenbush. From the Table of Contents: - If You Can't Beat 'Em, Join 'Em! - Hot Bottles Followed by Cold Wars - Games Infinite and Indefinite - Games Eternal--Games Entailed - Survival in the Lost World

Research from the neurosciences and behavioural sciences highlights the importance of individual differences in explaining human behaviour. Individual differences in core psychological constructs, such as intelligence or personality, account for meaningful variations in a vast range of responses and behaviours. Aspects of chess have been increasingly used in the past to evaluate a myriad of psychological theories, and several of these studies consider individual differences to be key constructs in their respective fields. This book summarizes the research surrounding the psychology of chess from an individual- differences perspective. The findings accumulated from nearly forty years' worth of research about chess and individual differences are brought together to show what is known - and still unknown - about the psychology of chess, with an emphasis on how people differ from one another.

This book introduces the theory and applications of uncertain optimal control, and establishes two types of models including expected value uncertain optimal control and optimistic value uncertain optimal control. These models, which have continuous-time forms and discrete-time forms, make use of dynamic programming. The uncertain optimal control theory relates to equations of optimality, uncertain bang-bang optimal control, optimal control with switched uncertain system, and optimal control for uncertain system with time-delay. Uncertain optimal control has applications in portfolio selection, engineering, and games. The book is a useful resource for researchers, engineers, and students in the fields of mathematics, cybernetics, operations research, industrial engineering, artificial intelligence, economics, and management science.

"Addresses the key topic in combinatorial synthesis--how to optimize the quality of a combinatorial library--by determining the usefulness of synthesized compunds, the reliability of biological assay results, and analyzing acadmic and industrial applications, real-world examples, and case studies of successful and unsuccessful technologies."

In a book sure to stir argument for years to come, Robert Wright challen+ges the conventional view that biological evolution and human history are aimless. Ingeniously employing game theory – the logic of ‘zero-sum’ and ‘non-zero-sum’ games – Wright isolates the impetus behind life’s basic direction: the impetus that, via biological evolution, created complex, intelligent animals, and then via cultural evolution, pushed the human species towards deeper and vaster social complexity. In this view, the coming of today’s independent global society was ‘in the cards’ – not quite inevitable, but, as Wright puts it, ‘so probable as to inspire wonder’. In a narrative of breathtaking scope and erudition, yet pungent wit, Wright takes on some of the past century’s most prominent thinkers, including Isaiah Berlin, Karl Popper, Stephen Jay Gould, and Richard Dawkins. Wright argues that a coolly specific appraisal of humanity’s three-billion-year past can give new spiritual meaning to the present and even offer political guidance for the future. This book will change the way people think about the human prospect.
 

Handbook of Optimization in Medicine is devoted to examining the dramatic increase in the application of effective optimization techniques to the delivery of health care. The articles, written by experts, focus on models and algorithms that have led to more efficient and sophisticated treatments of patients.

Topics covered include: optimization in medical imaging, classification and data mining with medical applications, treatment of epilepsy and other brain disorders, treatment of head-and-neck, prostate, and other cancers using conventional conformal and intensity-modulated radiation therapy as well as proton therapy, treatment selection for breast cancer based on new classification schemes, optimization for the genome project, optimal timing of organ transplants.

Known as the science of strategy, game theory is a branch of mathematics that has gained broad acceptance as a legitimate methodological tool, and has been widely adapted by a number of other fields. Frank C. Zagare provides an introduction to the application of game theory in the fields of security studies and diplomatic history, demonstrating the advantages of using a formal game-theoretic framework to explain complex events and strategic relationships. Comprised of three parts, the first illustrates the basic concepts of game theory, initially with abstract examples but later in the context of real world foreign policy decision-making. The author highlights the methodological problems of using game theory to construct an analytic narrative and the advantages of working around these obstacles. Part II develops three extended case studies that illustrate the theory at work: the First Moroccan Crisis of 1905-1906, the July Crisis of 1914, and the Cuban Missile Crisis of 1962. Finally, in Part III, Zagare describes a general theory of interstate conflict initiation, limitation, escalation, and resolution and rebuts criticisms of the methodology. Logically demanding, Game Theory, Diplomatic History and Security Studies conveys an intuitive understanding of the theory of games through the use of real-world examples to exemplify the 'theory in action'.

In this concise book based on his Arne Ryde Lectures in 2002, Young suggests a conceptual framework for studying strategic learning and highlights theoretical developments in the area. He discusses the interactive learning problem; reinforcement and regret; equilibrium; conditional no-regret learning; prediction, postdiction, and calibration; fictitious play and its variants; Bayesian learning; and hypothesis testing. Young's framework emphasizes the amount of information required to implement different types of learning rules, criteria for evaluating their performance, and alternative notions of equilibrium to which they converge. He also stresses the limits of what can be achieved: for a given type of game and a given amount of information, there may exist no learning procedure that satisfies certain reasonable criteria of performance and convergence. In short, Young has provided a valuable primer that delineates what we know, what we would like to know, and the limits of what we can know, when we try to learn about a system that is composed of other learners.

Many decision problems in Operations Research are defined on temporal networks, that is, workflows of time-consuming tasks whose processing order is constrained by precedence relations. For example, temporal networks are used to model projects, computer applications, digital circuits and production processes. Optimization problems arise in temporal networks when a decision maker wishes to determine a temporal arrangement of the tasks and/or a resource assignment that optimizes some network characteristic (e.g. the time required to complete all tasks). The parameters of these optimization problems (e.g. the task durations) are typically unknown at the time the decision problem arises. This monograph investigates solution techniques for optimization problems in temporal networks that explicitly account for this parameter uncertainty. We study several formulations, each of which requires different information about the uncertain problem parameters.