This book aims to contribute to the discussion about the implications of fuzzy logic, neural networks, digital era, and other intelligent techniques on organizations. This book will be very useful for academic researchers and postgraduate students aiming to introduce themselves to the field of quantitative techniques for overcoming uncertain environments and developing models to make decisions. Developments in other theories and socioeconomic and computational changes have shed light on the importance of fuzzy applications in social sciences. The treatment of uncertainty in the economic and business analysis is fundamental and requires instruments compatible with the uncertain environment of economics and business, because most of the traditional models have been overtaken by this reality when trying to make decisions with uncertain information. In the face of information technology, digitization, and uncertainty, organizations confront new opportunities and challenges. In order to take advantage of these opportunities and overcome current and future challenges, it is needed to understand the evolution of these phenomenon.

This open access book is an introduction to the regularity theory for free boundary problems. The focus is on the one-phase Bernoulli problem, which is of particular interest as it deeply influenced the development of the modern free boundary regularity theory and is still an object of intensive research. The exposition is organized around four main theorems, which are dedicated to the one-phase functional in its simplest form. Many of the methods and the techniques presented here are very recent and were developed in the context of different free boundary problems. We also give the detailed proofs of several classical results, which are based on some universal ideas and are recurrent in the free boundary, PDE and the geometric regularity theories. This book is aimed at graduate students and researches and is accessible to anyone with a moderate level of knowledge of elliptical PDEs.

Fractional evolution inclusions are an important form of differential inclusions within nonlinear mathematical analysis. They are generalizations of the much more widely developed fractional evolution equations (such as time-fractional diffusion equations) seen through the lens of multivariate analysis. Compared to fractional evolution equations, research on the theory of fractional differential inclusions is however only in its initial stage of development. This is important because differential models with the fractional derivative providing an excellent instrument for the description of memory and hereditary properties, and have recently been proved valuable tools in the modeling of many physical phenomena. The fractional order models of real systems are always more adequate than the classical integer order models, since the description of some systems is more accurate when the fractional derivative is used. The advantages of fractional derivatization become evident in modeling mechanical and electrical properties of real materials, description of rheological properties of rocks and in various other fields. Such models are interesting for engineers and physicists as well as so-called pure mathematicians. Phenomena investigated in hybrid systems with dry friction, processes of controlled heat transfer, obstacle problems and others can be described with the help of various differential inclusions, both linear and nonlinear. Fractional Evolution Equations and Inclusions is devoted to a rapidly developing area of the research for fractional evolution equations & inclusions and their applications to control theory. It studies Cauchy problems for fractional evolution equations, and fractional evolution inclusions with Hille-Yosida operators. It discusses control problems for systems governed by fractional evolution equations. Finally it provides an investigation of fractional stochastic evolution inclusions in Hilbert spaces.

This richly illustrated book introduces the subject of optimization to a broad audience with a balanced treatment of theory, models and algorithms. Through numerous examples from statistical learning, operations research, engineering, finance and economics, the text explains how to formulate and justify models while accounting for real-world considerations such as data uncertainty. It goes beyond the classical topics of linear, nonlinear and convex programming and deals with nonconvex and nonsmooth problems as well as games, generalized equations and stochastic optimization. The book teaches theoretical aspects in the context of concrete problems, which makes it an accessible onramp to variational analysis, integral functions and approximation theory. More than 100 exercises and 200 fully developed examples illustrate the application of the concepts. Readers should have some foundation in differential calculus and linear algebra. Exposure to real analysis would be helpful but is not prerequisite.

Following the successful PCS Auction conducted by the US Federal Communications Commission in 1994, auctions have replaced traditional ways of allocating valuable radio spectrum, a key resource for any mobile telecommunications operator. Spectrum auctions have raised billions of dollars worldwide and have become a role model for market-based approaches in the public and private sectors. The design of spectrum auctions is a central application of game theory and auction theory due to its importance in industry and the theoretical challenges it presents. Several auction formats have been developed with different properties addressing fundamental questions about efficiently selling multiple objects to a group of buyers. This comprehensive handbook features classic papers and new contributions by international experts on all aspects of spectrum auction design, including pros and cons of different auctions and lessons learned from theory, experiments, and the field, providing a valuable resource for regulators, telecommunications professionals, consultants, and researchers.

Modeling, Simulation, and Optimization of Supply Chains is an up-to-date introduction to the mathematical theory of supply chains, which focuses on those supply chain networks which are described by partial differential equations. The book discusses modeling of complex supply networks as well as their mathematical theory. In addition, the authors investigate the optimization of some of the discussed models and present the analytical and numerical results on optimization problems. Practical examples demonstrate the applicability of the presented approaches. The book provides an introduction to the topic and also explores the more advanced theoretical and numerical background. Graduate students and researchers, who wish to stay abreast of the latest developments in this field, will be interested in this book; it may be used to teach advanced courses on modeling of physical phenomena as well as introductory courses on supply chain theory.

Nonlinear Optimization of Vehicle Safety Structures: Modeling of Structures Subjected to Large Deformations provides a cutting-edge overview of the latest optimization methods for vehicle structural design. The book focuses on large deformation structural optimization algorithms and applications, covering the basic principles of modern day topology optimization and comparing the benefits and flaws of different algorithms in use. The complications of non-linear optimization are highlighted, along with the shortcomings of recently proposed algorithms. Using industry relevant case studies, users will how optimization software can be used to address challenging vehicle safety structure problems and how to explore the limitations of the approaches given. The authors draw on research work with the likes of MIRA, Jaguar Land Rover and Tata Motors European Technology Centre as part of multi-million pound European funded research projects, emphasizing the industry applications of recent advances. The book is intended for crash engineers, restraints system engineers and vehicle dynamics engineers, as well as other mechanical, automotive and aerospace engineers, researchers and students with a structural focus.

This textbook offers a concise yet rigorous introduction to calculus of variations and optimal control theory, and is a self-contained resource for graduate students in engineering, applied mathematics, and related subjects. Designed specifically for a one-semester course, the book begins with calculus of variations, preparing the ground for optimal control. It then gives a complete proof of the maximum principle and covers key topics such as the Hamilton-Jacobi-Bellman theory of dynamic programming and linear-quadratic optimal control.

"Calculus of Variations and Optimal Control Theory" also traces the historical development of the subject and features numerous exercises, notes and references at the end of each chapter, and suggestions for further study.Offers a concise yet rigorous introduction Requires limited background in control theory or advanced mathematics Provides a complete proof of the maximum principle Uses consistent notation in the exposition of classical and modern topics Traces the historical development of the subject Solutions manual (available only to teachers)

Leading universities that have adopted this book include: University of Illinois at Urbana-Champaign ECE 553: Optimum Control Systems Georgia Institute of Technology ECE 6553: Optimal Control and Optimization University of Pennsylvania ESE 680: Optimal Control Theory University of Notre Dame EE 60565: Optimal Control

Evolutionary computation algorithms are employed to minimize functions with large number of variables. Biogeography-based optimization (BBO) is an optimization algorithm that is based on the science of biogeography, which researches the migration patterns of species. These migration paradigms provide the main logic behind BBO. Due to the cross-disciplinary nature of the optimization problems, there is a need to develop multiple approaches to tackle them and to study the theoretical reasoning behind their performance. This book explains the mathematical model of BBO algorithm and its variants created to cope with continuous domain problems (with and without constraints) and combinatorial problems.

Provides well-written self-contained chapters, including problem sets and exercises, making it ideal for the classroom setting; Introduces applied optimization to the hazardous waste blending problem; Explores linear programming, nonlinear programming, discrete optimization, global optimization, optimization under uncertainty, multi-objective optimization, optimal control and stochastic optimal control; Includes an extensive bibliography at the end of each chapter and an index; GAMS files of case studies for Chapters 2, 3, 4, 5, and 7 are linked to http://www.springer.com/math/book/978-0-387-76634-8; Solutions manual available upon adoptions.

Game theory is central to understanding human behavior and relevant to all of the behavioral sciences--from biology and economics, to anthropology and political science. However, as "The Bounds of Reason" demonstrates, game theory alone cannot fully explain human behavior and should instead complement other key concepts championed by the behavioral disciplines. Herbert Gintis shows that just as game theory without broader social theory is merely technical bravado, so social theory without game theory is a handicapped enterprise. This edition has been thoroughly revised and updated.

Reinvigorating game theory, "The Bounds of Reason" offers innovative thinking for the behavioral sciences.

A wealth of research in recent decades has seen the economic approach to human behavior extended over many areas previously considered to belong to sociology, political science, law, and other fields. Research has also shown that economics can provide insight into many aspects of sports, including soccer. Beautiful Game Theory is the first book that uses soccer to test economic theories and document novel human behavior. In this brilliant and entertaining book, Ignacio Palacios-Huerta illuminates economics through the world's most popular sport. He offers unique and often startling insights into game theory and microeconomics, covering topics such as mixed strategies, discrimination, incentives, and human preferences. He also looks at finance, experimental economics, behavioral economics, and neuroeconomics. Soccer provides rich data sets and environments that shed light on universal economic principles in interesting and useful ways. Essential reading for students, researchers, and sports enthusiasts, Beautiful Game Theory is the first book to show what soccer can do for economics.

The absence of derivatives, often combined with the presence of noise or lack of smoothness, is a major challenge for optimization. This book explains how sampling and model techniques are used in derivative-free methods and how these methods are designed to efficiently and rigorously solve optimization problems. Although readily accessible to readers with a modest background in computational mathematics, it is also intended to be of interest to researchers in the field. Introduction to Derivative-Free Optimization is the first contemporary comprehensive treatment of optimization without derivatives. This book covers most of the relevant classes of algorithms from direct search to model-based approaches. It contains a comprehensive description of the sampling and modeling tools needed for derivative-free optimization; these tools allow the reader to better understand the convergent properties of the algorithms and identify their differences and similarities. Introduction to Derivative-Free Optimization also contains analysis of convergence for modified Nelder-Mead and implicit-filtering methods, as well as for model-based methods such as wedge methods and methods based on minimum-norm Frobenius models.

The Selfish Gene is a classic exposition of evolutionary thought. In it Professor Dawkins articulates a gene's eye view of evolution - a view giving centre stage to these persistent units of information, and in which organisms can be seen as vehicles for the replication of genes. The book provoked widespread and heated debate, which in part led Dawkins to write The Extended Phenotype, in which he gave a deeper clarification of the central concept of the gene as the unit of selection, as well as contributing his own development of this insight. For the first time, The Extended Selfish Gene brings these two books together, by including two key chapters from The Extended Phenotype. These chapters provide Dawkins's detailed and powerful response to two issues raised by critics of The Selfish Gene: the accusations of genetic determinism (the idea that our behaviour is entirely determined by our genes), and of "adaptationism " (that all traits are indiscriminately perceived to be adaptations resulting from natural selection). While written in particular for the biology community, Dawkins's clarity of expression allows these chapters to be accessible to all who are seriously engaged with the gene's eye view and its implications. The imaginative, powerful, and stylistically brilliant Selfish Gene not only brought the insights of Neo-Darwinism to a wide audience, but galvanized the biology community, generating much debate and stimulating whole new areas of research. Forty years later, its insights remain as significant as on the day it was published. Along with the two extra chapters, The Extended Selfish Gene includes a new epilogue to The Selfish Gene from the author which highlights the relevance of the gene's eye view to evolutionary biology today.

This textbook on Linear and Nonlinear Optimization is intended for graduate and advanced undergraduate students in operations research and related fields. It is both literate and mathematically strong, yet requires no prior course in optimization. As suggested by its title, the book is divided into two parts covering in their individual chapters LP Models and Applications; Linear Equations and Inequalities; The Simplex Algorithm; Simplex Algorithm Continued; Duality and the Dual Simplex Algorithm; Postoptimality Analyses; Computational Considerations; Nonlinear (NLP) Models and Applications; Unconstrained Optimization; Descent Methods; Optimality Conditions; Problems with Linear Constraints; Problems with Nonlinear Constraints; Interior-Point Methods; and an Appendix covering Mathematical Concepts. Each chapter ends with a set of exercises. The book is based on lecture notes the authors have used in numerous optimization courses the authors have taught at Stanford University. It emphasizes modeling and numerical algorithms for optimization with continuous (not integer) variables. The discussion presents the underlying theory without always focusing on formal mathematical proofs (which can be found in cited references). Another feature of this book is its inclusion of cultural and historical matters, most often appearing among the footnotes. "This book is a real gem. The authors do a masterful job of rigorously presenting all of the relevant theory clearly and concisely while managing to avoid unnecessary tedious mathematical details. This is an ideal book for teaching a one or two semester masters-level course in optimization - it broadly covers linear and nonlinear programming effectively balancing modeling, algorithmic theory, computation, implementation, illuminating historical facts, and numerous interesting examples and exercises. Due to the clarity of the exposition, this book also serves as a valuable reference for self-study." Professor Ilan Adler, IEOR Department, UC Berkeley "A carefully crafted introduction to the main elements and applications of mathematical optimization. This volume presents the essential concepts of linear and nonlinear programming in an accessible format filled with anecdotes, examples, and exercises that bring the topic to life. The authors plumb their decades of experience in optimization to provide an enriching layer of historical context. Suitable for advanced undergraduates and masters students in management science, operations research, and related fields."Michael P. Friedlander, IBM Professor of Computer Science, Professor of Mathematics, University of British Columbia

Questo libro di testo di ottimizzazione combinatoria pone in particolare risalto i

risultati teorici e gli algoritmi che, al contrario delle euristiche, hanno una garanzia

di avere buone prestazioni. Comprende una vasta scelta di argomenti e nasce

come riferimento di diversi corsi di ottimizzazione combinatoria sia di base che di

livello avanzato. Il libro contiene dimostrazioni complete (ma concise) anche

di molti risultati avanzati, alcuni dei quali non sono mai apparsi prima in un libro.

Vengono anche trattati molti dei temi di ricerca piu attuali e sono riportati molti

riferimenti alla letteratura. Quindi questo libro, traduzione della quarta edizione in lingua originale, rappresenta lo stato dell'arte dell'ottimizzazione combinatoria.

This book presents the theory and practical applications of the Master equation approach, which provides a powerful general framework for model building in a variety of disciplines. The aim of the book is to not only highlight different mathematical solution methods, but also reveal their potential by means of practical examples. Part I of the book, which can be used as a toolbox, introduces selected statistical fundamentals and solution methods for the Master equation. In Part II and Part III, the Master equation approach is applied to important applications in the natural and social sciences. The case studies presented mainly hail from the social sciences, including urban and regional dynamics, population dynamics, dynamic decision theory, opinion formation and traffic dynamics; however, some applications from physics and chemistry are treated as well, underlining the interdisciplinary modelling potential of the Master equation approach. Drawing upon the author's extensive teaching and research experience and consulting work, the book offers a valuable guide for researchers, graduate students and professionals alike.

What is a game? Classically, a game is perceived as something played by human beings. Its mathematical analysis is human-centered, explores the structures of particular games, economic or social environments and tries to model supposedly 'rational' human behavior in search of appropriate 'winning strategies'. This point of view places game theory into a very special scientific corner where mathematics, economics and psychology overlap and mingle.This book takes a novel approach to the subject. Its focus is on mathematical models that apply to game theory in particular but exhibit a universal character and thus extend the scope of game theory considerably.This textbook addresses anyone interested in a general game-theoretic view of the world. The reader should have mathematical knowledge at the level of a first course in real analysis and linear algebra. However, possibly more specialized aspects are further elaborated and pointers to relevant supplementary literature are given. Moreover, many examples invite the reader to participate 'actively' when going through the material. The scope of the book can be covered in one course on Mathematical Game Theory at advanced undergraduate or graduate level.

La finanza matematica ha visto un notevole sviluppo in tempi recenti, soprattutto per l'introduzione di strumenti finanziari atti a contenere il rischio nelle operazioni di mercato. Lo studio delle problematiche legate a tali strumenti richiede tecniche matematiche talvolta sofisticate e la maggior parte di queste tecniche sono legate alla teoria della Probabilita.
Gli ambienti finanziari sono quindi divenuti uno sbocco professionale non solo per gli economisti, ma anche per i matematici ed in generale per i laureati delle discipline tecnico-scientifiche. Il presente libro e inteso come testo e nasce dall'esperienza d insegnamento degli autori. Non esistono molti testi simili a livello internazionale ed il libro intende colmare tale lacuna. Benche concepito maggiormente per un corso di laurea triennale in matematica, esso dovrebbe adattarsi bene anche a corsi di tipo quantitativo per le facolta di economia. La struttura del testo e originata dall'idea di insegnare per esempi e contro-esempi. Si e pero poi sviluppata in un testo completo che contiene anche la teoria. A differenza pero di altri libri di teoria, questo libro contiene numerosi esempi ed esercizi risolti. Il testo e suddiviso in quattro parti in cui vengono trattati i seguenti argomenti: valutazione e copertura di derivati Europei, ottimizzazione di portafoglio (programmazione dinamica e metodi martingala), valutazione e copertura di derivati Americani, modelli multi-periodali per i tassi d'interesse. In ogni parte, dopo una presentazione sintetica ma completa della teoria, vengono proposti numerosi esercizi di cui e fornita la dettagliata risoluzione."

The Great War is an immense, confusing and overwhelming historical conflict - the ideal case study for teaching game theory and international relations. Using thirteen historical puzzles, from the outbreak of the war and the stability of attrition, to unrestricted submarine warfare and American entry into the war, this book provides students with a rigorous yet accessible training in game theory. Each chapter shows, through guided exercises, how game theoretical models can explain otherwise challenging strategic puzzles, shedding light on the role of individual leaders in world politics, cooperation between coalitions partners, the effectiveness of international law, the termination of conflict, and the challenges of making peace. Its analytical history of World War I also surveys cutting edge political science research on international relations and the causes of war. Written by a leading game theorist known for his expertise of the war, this textbook includes useful student features such as chapter key terms, contemporary maps, a timeline of events, a list of key characters and additional end-of-chapter game-theoretic exercises.

Practical Financial Optimization is a comprehensive guide to optimization techniques in financial decision making. This book illuminates the relationship between theory and practice, providing the readers with solid foundational knowledge.* Focuses on classical static mean-variance analysis and portfolio immunization, scenario-based models, multi-period dynamic portfolio optimization, and the relationships between classes of models* Analyizes real world applications and implications for financial engineers* Includes a list of models and a section on notations that includes a glossary of symbols and abbreviations

Human communication can be characterized in terms of game theory as competing motivations in a social game in which one person desires "winning" in terms of obtaining compliance. Furthermore, game theory is an interesting framework for dialogue modeling, both the human dialogue and the human-machine dialogue. The first chapter describes the author's contribution on the pragmatics of the dialogue, and proposes a general model of dialogue based on game theory. The second and third chapters review game theory as a way to analyze many different kinds of decisions and decision problems. The remaining chapters present a methodology based on Decision Analysis; decisions in everyday statistics; and an analysis of Thomas Bayes' famous "Essay towards Solving a Problem in the Doctrine of Chances".