Combinatorial optimization is a multidisciplinary scientific area, lying in the interface of three major scientific domains: mathematics, theoretical computer science and management. The three volumes of the Combinatorial Optimization series aim to cover a wide range of topics in this area. These topics also deal with fundamental notions and approaches as with several classical applications of combinatorial optimization. Concepts of Combinatorial Optimization, is divided into three parts: - On the complexity of combinatorial optimization problems, presenting basics about worst-case and randomized complexity; - Classical solution methods, presenting the two most-known methods for solving hard combinatorial optimization problems, that are Branch-and-Bound and Dynamic Programming; - Elements from mathematical programming, presenting fundamentals from mathematical programming based methods that are in the heart of Operations Research since the origins of this field.

Optimization techniques have developed into a modern-day solution for real-world problems in various industries. As a way to improve performance and handle issues of uncertainty, optimization research becomes a topic of special interest across disciplines. Problem Solving and Uncertainty Modeling through Optimization and Soft Computing Applications presents the latest research trends and developments in the area of applied optimization methodologies and soft computing techniques for solving complex problems. Taking a multi-disciplinary approach, this critical publication is an essential reference source for engineers, managers, researchers, and post-graduate students.

Through analysis of three case study videogames - Left 4 Dead 2, DayZ and Minecraft - and their online player communities, Digital Zombies, Undead Stories develops a framework for understanding how collective gameplay generates experiences of narrative, as well as the narrative dimensions of players' creative activity on social media platforms. Narrative emergence is addressed as a powerful form of player experience in multiplayer games, one which makes individual games' boundaries and meanings fluid and negotiable by players. The phenomenon is also shown to be recursive in nature, shaping individual and collective understandings of videogame texts over time. Digital Zombies, Undead Stories focuses on games featuring zombies as central antagonists. The recurrent figure of the videogame zombie, which mediates between chaos and rule-driven predictability, serves as both metaphor and mascot for narrative emergence. This book argues that in the zombie genre, emergent experiences are at the heart of narrative experiences for players, and more broadly demonstrates the potential for the phenomenon to be understood as a fundamental part of everyday play experiences across genres.

Combinatorial optimization is a multidisciplinary scientific area, lying in the interface of three major scientific domains: mathematics, theoretical computer science and management. The three volumes of the Combinatorial Optimization series aim to cover a wide range of topics in this area. These topics also deal with fundamental notions and approaches as with several classical applications of combinatorial optimization. Concepts of Combinatorial Optimization, is divided into three parts: - On the complexity of combinatorial optimization problems, presenting basics about worst-case and randomized complexity; - Classical solution methods, presenting the two most-known methods for solving hard combinatorial optimization problems, that are Branch-and-Bound and Dynamic Programming; - Elements from mathematical programming, presenting fundamentals from mathematical programming based methods that are in the heart of Operations Research since the origins of this field.

This book presents the state-of-the-art methods in Linear Integer Programming, including some new algorithms and heuristic methods developed by the authors in recent years. Topics as Characteristic equation (CE), application of CE to bi-objective and multi-objective problems, Binary integer problems, Mixed-integer models, Knapsack models, Complexity reduction, Feasible-space reduction, Random search, Connected graph are also treated.

The advent of the internet largely changed the landscape of marketing to adopt a wide variety of communication techniques and creative selling on virtual platforms. Gaming provides a highly pervasive and influential mode of offering new media communication to consumers that can be further improved by digital innovation. Application of Gaming in New Media Marketing is a collection of vital research on the methods and applications of gaming in marketing, including its growth, recent trends, practices, issues, and main challenges. Highlighting a range of topics including digital advertising, media planning, and social media marketing, this book is ideally designed for marketers, software developers, managers, business researchers, academicians, and graduate-level students seeking current research on new and innovative methods to reach and connect with audiences through games in a highly interactive, measurable, and focused way.

The book systematically introduces smart power system design and its infrastructure, platform and operating standards. It focuses on multi-objective optimization and illustrates where the intelligence of the system lies. With abundant project data, this book is a practical guideline for engineers and researchers in electrical engineering, as well as power network designers and managers in administration.

This is a guide, in theory and in practice, to how current technological changes have impacted our interaction with texts and with each other. Henry Sussman rereads pivotal moments in literary, philosophical and cultural modernity as anticipating the cybernetic discourse that has increasingly defined theory since the computer revolution. Cognitive science, psychoanalysis and systems theory are paralleled to current trends in literary and philosophical theory. Chapters alternate between theory and readings of literary texts, resulting in a broad but rigorously grounded framework for the relation between literature and computer science. This book is a refreshing perspective on the analog-orientated tradition of theory in the humanities - and offers the first literary-textual genealogy of the digital.

This bookdescribes computational financetools. It covers fundamental numerical analysis and computational techniques, such asoption pricing, and givesspecial attention tosimulation and optimization. Many chapters are organized as case studies aroundportfolio insurance and risk estimation problems. In particular, several chapters explain optimization heuristics and how to use them for portfolio selection and in calibration of estimation and option pricing models. Such practical examples allow readers to learn the steps for solving specific problems and apply these steps to others. At the same time, the applications are relevant enough to make the book a useful reference. Matlab and R sample code is provided in the text and can be downloaded from the book's website.
Shows ways to build and implement tools that help test ideasFocuses on the application of heuristics; standard methods receive limited attentionPresents as separate chapters problems from portfolio optimization, estimation of econometric models, and calibration of option pricing models"

In everyday life we must often reach decisions while knowing that the outcome will not only depend on our own choice, but also on the choices of others. These situations are the focus of epistemic game theory. Unlike classical game theory, it explores how people may reason about their opponents before they make their final choice in a game. Packed with examples and practical problems based on stories from everyday life, this is the first textbook to explain the principles of epistemic game theory. Each chapter is dedicated to one particular, natural way of reasoning. The book then shows how each of these ways of reasoning will affect the final choices that can rationally be made and how these choices can be found by iterative procedures. Moreover, it does so in a way that uses elementary mathematics and does not presuppose any previous knowledge of game theory.

The rich, multi-faceted and multi-disciplinary field of matching-based market design is an active and important one due to its highly successful applications with economic and sociological impact. Its home is economics, but with intimate connections to algorithm design and operations research. With chapters contributed by over fifty top researchers from all three disciplines, this volume is unique in its breadth and depth, while still being a cohesive and unified picture of the field, suitable for the uninitiated as well as the expert. It explains the dominant ideas from computer science and economics underlying the most important results on market design and introduces the main algorithmic questions and combinatorial structures. Methodologies and applications from both the pre-Internet and post-Internet eras are covered in detail. Key chapters discuss the basic notions of efficiency, fairness and incentives, and the way market design seeks solutions guided by normative criteria borrowed from social choice theory.

Congruences are ubiquitous in computer science, engineering, mathematics, and related areas. Developing techniques for finding (the number of) solutions of congruences is an important problem. But there are many scenarios in which we are interested in only a subset of the solutions; in other words, there are some restrictions. What do we know about these restricted congruences, their solutions, and applications? This book introduces the tools that are needed when working on restricted congruences and then systematically studies a variety of restricted congruences. Restricted Congruences in Computing defines several types of restricted congruence, obtains explicit formulae for the number of their solutions using a wide range of tools and techniques, and discusses their applications in cryptography, information security, information theory, coding theory, string theory, quantum field theory, parallel computing, artificial intelligence, computational biology, discrete mathematics, number theory, and more. This is the first book devoted to restricted congruences and their applications. It will be of interest to graduate students and researchers across computer science, electrical engineering, and mathematics.

Computer science and economics have engaged in a lively interaction over the past fifteen years, resulting in the new field of algorithmic game theory. Many problems that are central to modern computer science, ranging from resource allocation in large networks to online advertising, involve interactions between multiple self-interested parties. Economics and game theory offer a host of useful models and definitions to reason about such problems. The flow of ideas also travels in the other direction, and concepts from computer science are increasingly important in economics. This book grew out of the author's Stanford University course on algorithmic game theory, and aims to give students and other newcomers a quick and accessible introduction to many of the most important concepts in the field. The book also includes case studies on online advertising, wireless spectrum auctions, kidney exchange, and network management.

Computational fluid dynamics (CFD) and optimal shape design (OSD) are of practical importance for many engineering applications - the aeronautic, automobile, and nuclear industries are all major users of these technologies.
Giving the state of the art in shape optimization for an extended range of applications, this new edition explains the equations needed to understand OSD problems for fluids (Euler and Navier Strokes, but also those for microfluids) and covers numerical simulation techniques. Automatic differentiation, approximate gradients, unstructured mesh adaptation, multi-model configurations, and time-dependent problems are introduced, illustrating how these techniques are implemented within the industrial environments of the aerospace and automobile industries.
With the dramatic increase in computing power since the first edition, methods that were previously unfeasible have begun giving results. The book remains primarily one on differential shape optimization, but the coverage of evolutionary algorithms, topological optimization methods, and level set algortihms has been expanded so that each of these methods is now treated in a separate chapter.
Presenting a global view of the field with simple mathematical explanations, coding tips and tricks, analytical and numerical tests, and exhaustive referencing, the book will be essential reading for engineers interested in the implementation and solution of optimization problems. Whether using commercial packages or in-house solvers, or a graduate or researcher in aerospace or mechanical engineering, fluid dynamics, or CFD, the second edition will help the reader understand and solve design problems in this exciting area of research and development, and will prove especially useful in showing how to apply the methodology to practical problems.

Mathematical optimization is used in nearly all computer graphics applications, from computer vision to animation. This book teaches readers the core set of techniques that every computer graphics professional should understand in order to envision and expand the boundaries of what is possible in their work.
Study of this authoritative reference will help readers develop a very powerful tool- the ability to create and decipher mathematical models that can better realize solutions to even the toughest problems confronting computer graphics community today.
The authors are renowned researchers from IMPA, the Brazilian National Institute for Pure and Applied Mathematics.
*Distils down a vast and complex world of info on optimization into one short, self-contained volume especially for computer graphics
*Helps CG professionals identify the best technique for solving particular problems quickly, by categorizing the most effective algorithms by application
*Keeps readers current by supplementing the focus on key, classic methods with special end-of-chapter sections on cutting-edge developments

Game theory means rigorous strategic thinking. It s the art of anticipating your opponent s next moves, knowing full well that your rival is trying to do the same thing to you. Though parts of game theory involve simple common sense, much is counterintuitive, and it can only be mastered by developing a new way of seeing the world. Using a diverse array of rich case studies from pop culture, TV, movies, sports, politics, and history the authors show how nearly every business and personal interaction has a game-theory component to it. Mastering game theory will make you more successful in business and life, and this lively book is the key to that mastery."

This book provides an overview of radar waveform synthesis obtained as the result of computational optimization processes and covers the most challenging application fields. The book balances a practical point of view with a rigorous mathematical approach corroborated with a wealth of numerical study cases and some real experiments. Additionally, the book has a cross-disciplinary approach because it exploits cross-fertilization with the recent research and discoveries in optimization theory. The material of the book is organized into ten chapters, each one completed with a comprehensive list of references. The following topics are covered: recent advances of binary sequence designs and their applications; quadratic optimization for unimodular sequence synthesis and applications; a computational design of phase-only (possibly binary) sequences for radar systems; constrained radar code design for spectrally congested environments via quadratic optimization; robust transmit code and receive filter design for extended targets detection in clutter; optimizing radar transceiver for Doppler processing via non-convex programming; radar waveform design via the majorization-minimization framework; Lagrange programming neural network for radar waveform design; cognitive local ambiguity function shaping with spectral coexistence and experiments; and relative entropy based waveform design for MIMO radar. Targeted at an audience of radar engineers and researchers, this book provides thorough and up-to-date coverage of optimisation theory for radar waveform design.

This book is devoted to game theory and its applications to environmental problems, economics, and management. It collects contributions originating from the 12th International Conference on "Game Theory and Management" 2018 (GTM2018) held at Saint Petersburg State University, Russia, from 27 to 29 June 2018.

This publication contributes to the serious games field by investigating original contributions and methods that use serious games in various domains. This comprehensive and timely publication works as an essential reference source, building on the available literature in the field of Serious Games for the economic and social development of countries while providing for further research opportunities in this dynamic and growing field. Thus, the book provides the opportunity for a reflection on this important issue, increasing the understanding of the importance of Serious Games in the context of organizations' improvements, providing relevant academic work, empirical research findings, and an overview of this relevant field of study. This text provides the resources necessary for policy makers, technology developers and managers to adopt and implement solutions for a more digital era.

It has widely been recognized that submodular functions play essential roles in efficiently solvable combinatorial optimization problems. Since the publication of the 1st edition of this book fifteen years ago, submodular functions have been showing further increasing importance in optimization, combinatorics, discrete mathematics, algorithmic computer science, and algorithmic economics, and there have been made remarkable developments of theory and algorithms in submodular functions. The 2nd edition of the book supplements the 1st edition with a lot of remarks and with new two chapters: "Submodular Function Minimization" and "Discrete Convex Analysis." The present 2nd edition is still a unique book on submodular functions, which is essential to students and researchers interested in combinatorial optimization, discrete mathematics, and discrete algorithms in the fields of mathematics, operations research, computer science, and economics.

Key features:

- Self-contained exposition of the theory of submodular functions.
- Selected up-to-date materials substantial to future developments.
- Polyhedral description of Discrete Convex Analysis.
- Full description of submodular function minimization algorithms.
- Effective insertion of figures.
- Useful in applied mathematics, operations research, computer science, and economics.
- Self-contained exposition of the theory of submodular functions.
- Selected up-to-date materials substantial to future developments.
- Polyhedral description of Discrete Convex Analysis.
- Full description of submodular function minimization algorithms.
- Effective insertion of figures.
- Useful in applied mathematics, operations research, computer science, and economics.

The engineering and business problems the world faces today have become more impenetrable and unstructured, making the design of a satisfactory problem-specific algorithm nontrivial. Modeling, Analysis, and Applications in Metaheuristic Computing: Advancements and Trends is a collection of the latest developments, models, and applications within the transdisciplinary fields related to metaheuristic computing. Providing researchers, practitioners, and academicians with insight into a wide range of topics such as genetic algorithms, differential evolution, and ant colony optimization, this book compiles the latest findings, analysis, improvements, and applications of technologies within metaheuristic computing.