In an expanding world with limited resources, optimization and uncertainty quantification have become a necessity when handling complex systems and processes. This book provides the foundational material necessary for those who wish to embark on advanced research at the limits of computability, collecting together lecture material from leading experts across the topics of optimization, uncertainty quantification and aerospace engineering. The aerospace sector in particular has stringent performance requirements on highly complex systems, for which solutions are expected to be optimal and reliable at the same time. The text covers a wide range of techniques and methods, from polynomial chaos expansions for uncertainty quantification to Bayesian and Imprecise Probability theories, and from Markov chains to surrogate models based on Gaussian processes. The book will serve as a valuable tool for practitioners, researchers and PhD students.

This book addresses the principles and applications of metaheuristic approaches in engineering and related fields. The first part covers metaheuristics tools and techniques such as ant colony optimization and Tabu search, and their applications to several classes of optimization problems. In turn, the book's second part focuses on a wide variety of metaheuristics applications in engineering and/or the applied sciences, e.g. in smart grids and renewable energy. In addition, the simulation codes for the problems discussed are included in an appendix for ready reference. Intended for researchers aspiring to learn and apply metaheuristic techniques, and gathering contributions by prominent experts in the field, the book offers readers an essential introduction to metaheuristics, its theoretical aspects and applications.

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.

This textbook treats graph colouring as an algorithmic problem, with a strong emphasis on practical applications. The author describes and analyses some of the best-known algorithms for colouring graphs, focusing on whether these heuristics can provide optimal solutions in some cases; how they perform on graphs where the chromatic number is unknown; and whether they can produce better solutions than other algorithms for certain types of graphs, and why. The introductory chapters explain graph colouring, complexity theory, bounds and constructive algorithms. The author then shows how advanced, graph colouring techniques can be applied to classic real-world operational research problems such as designing seating plans, sports scheduling, and university timetabling. He includes many examples, suggestions for further reading, and historical notes, and the book is supplemented by an online suite of downloadable code. The book is of value to researchers, graduate students, and practitioners in the areas of operations research, theoretical computer science, optimization, and computational intelligence. The reader should have elementary knowledge of sets, matrices, and enumerative combinatorics.

This book presents the latest trends and developments in multimodal optimization and niching techniques. Most existing optimization methods are designed for locating a single global solution. However, in real-world settings, many problems are "multimodal" by nature, i.e., multiple satisfactory solutions exist. It may be desirable to locate several such solutions before deciding which one to use. Multimodal optimization has been the subject of intense study in the field of population-based meta-heuristic algorithms, e.g., evolutionary algorithms (EAs), for the past few decades. These multimodal optimization techniques are commonly referred to as "niching" methods, because of the nature-inspired "niching" effect that is induced to the solution population targeting at multiple optima. Many niching methods have been developed in the EA community. Some classic examples include crowding, fitness sharing, clearing, derating, restricted tournament selection, speciation, etc. Nevertheless, applying these niching methods to real-world multimodal problems often encounters significant challenges. To facilitate the advance of niching methods in facing these challenges, this edited book highlights the latest developments in niching methods. The included chapters touch on algorithmic improvements and developments, representation, and visualization issues, as well as new research directions, such as preference incorporation in decision making and new application areas. This edited book is a first of this kind specifically on the topic of niching techniques. This book will serve as a valuable reference book both for researchers and practitioners. Although chapters are written in a mutually independent way, Chapter 1 will help novice readers get an overview of the field. It describes the development of the field and its current state and provides a comparative analysis of the IEEE CEC and ACM GECCO niching competitions of recent years, followed by a collection of open research questions and possible research directions that may be tackled in the future.

This book discusses systematic designs of stable adaptive fuzzy logic controllers employing hybridizations of Lyapunov strategy-based approaches/H theory-based approaches and contemporary stochastic optimization techniques. The text demonstrates how candidate stochastic optimization techniques like Particle swarm optimization (PSO), harmony search (HS) algorithms, covariance matrix adaptation (CMA) etc. can be utilized in conjunction with the Lyapunov theory/H theory to develop such hybrid control strategies. The goal of developing a series of such hybridization processes is to combine the strengths of both Lyapunov theory/H theory-based local search methods and stochastic optimization-based global search methods, so as to attain superior control algorithms that can simultaneously achieve desired asymptotic performance and provide improved transient responses. The book also demonstrates how these intelligent adaptive control algorithms can be effectively utilized in real-life applications such as in temperature control for air heater systems with transportation delay, vision-based navigation of mobile robots, intelligent control of robot manipulators etc.

One of the most frequently occurring types of optimization problems involves decision variables which have to take integer values. From a practical point of view, such problems occur in countless areas of management, engineering, administration, etc., and include such problems as location of plants or warehouses, scheduling of aircraft, cutting raw materials to prescribed dimensions, design of computer chips, increasing reliability or capacity of networks, etc. This is the class of problems known in the professional literature as "discrete optimization" problems. While these problems are of enormous applicability, they present many challenges from a computational point of view. This volume is an update on the impressive progress achieved by mathematicians, operations researchers, and computer scientists in solving discrete optimization problems of very large sizes. The surveys in this volume present a comprehensive overview of the state of the art in discrete optimization and are written by the most prominent researchers from all over the world.

This volume describes the tremendous progress in discrete optimization achieved in the last 20 years since the publication of Discrete Optimization '77, Annals of Discrete Mathematics, volumes 4 and 5, 1979 (Elsevier). It contains surveys of the state of the art written by the most prominent researchers in the field from all over the world, and covers topics like neighborhood search techniques, lift and project for mixed 0-1 programming, pseudo-Boolean optimization, scheduling and assignment problems, production planning, location, bin packing, cutting planes, vehicle routing, and applications to graph theory, mechanics, chip design, etc.

Key features:
state of the art surveys
comprehensiveness
prominent authors
theoretical, computational and applied aspects.

This book is a reprint of "Discrete Applied Mathematics" Volume 23, Numbers 1-3
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The relaxation method has enjoyed an intensive development during many decades and this new edition of this comprehensive text reflects in particular the main achievements in the past 20 years. Moreover, many further improvements and extensions are included, both in the direction of optimal control and optimal design as well as in numerics and applications in materials science, along with an updated treatment of the abstract parts of the theory.

There is an enhanced level of connectivity available in modern society through the increased usage of various technological devices. Such developments have led to the integration of smart objects into the Internet of Things (IoT), an emerging paradigm in the digital age. Game Theory Solutions for the Internet of Things: Emerging Research and Opportunities examines the latest strategies for the management of IoT systems and the application of theoretical models to enhance real-world applications and improve system efficiency. Highlighting innovative algorithms and methods, as well as coverage on cloud computing, cross-domain applications, and energy control, this book is a pivotal source of information for researchers, practitioners, graduate students, professionals, and academics interested in the game theoretic solutions for IoT applications.

MATRIX is Australia's international, residential mathematical research institute. It facilitates new collaborations and mathematical advances through intensive residential research programs, each lasting 1-4 weeks. This book is a scientific record of the five programs held at MATRIX in its first year, 2016: - Higher Structures in Geometry and Physics - Winter of Disconnectedness - Approximation and Optimisation - Refining C*-Algebraic Invariants for Dynamics using KK-theory - Interactions between Topological Recursion, Modularity, Quantum Invariants and Low- dimensional Topology The MATRIX Scientific Committee selected these programs based on their scientific excellence and the participation rate of high-profile international participants. Each program included ample unstructured time to encourage collaborative research; some of the longer programs also included an embedded conference or lecture series. The articles are grouped into peer-reviewed contributions and other contributions. The peer-reviewed articles present original results or reviews on selected topics related to the MATRIX program; the remaining contributions are predominantly lecture notes based on talks or activities at MATRIX.

The book aims at describing the recent developments in the existence and stability of Nash equilibrium. The two topics are central to game theory and economics and have been extensively researched. Recent results on existence and stability of Nash equilibrium are scattered and the relationship between them has not been explained clearly. The book will make these results easily accessible and understandable to researchers in the field.

This book presents the latest research in the fields of reliability theory and its applications, providing a comprehensive overview of reliability engineering and discussing various tools, techniques, strategies and methods within these areas. Reliability analysis is one of the most multidimensional topics in the field of systems reliability engineering, and while its rapid development creates opportunities for industrialists and academics, it is also means that it is hard to keep up to date with the research taking place. By gathering findings from institutions around the globe, the book offers insights into the international developments in the field. As well as discussing the current areas of research, it also identifies knowledge gaps in reliability theory and its applications and highlights fruitful avenues for future research. Covering topics from life cycle sustainability to performance analysis of cloud computing, this book is ideal for upper undergraduate and postgraduate researchers studying reliability engineering.

Building on the success of the first edition, Game Theory and Public Policy, Second Edition provides a critical, selective review of key concepts in game theory with a view to their applications in public policy. The author further suggests modifications for some of the models (chiefly in cooperative game theory) to improve their applicability to economics and public policy. Roger McCain makes use of the analytical tools of game theory for the pragmatic purpose of identifying problems and exploring potential solutions, providing a toolkit for the analysis of public policy allowing for a clearer understanding of the public policy enterprise itself. His critical review of major topics from both cooperative and non-cooperative game theory includes less-known ideas and constructive proposals for new approaches. This revised edition features a new second half that focuses on biform games, combining cooperative and non-cooperative decisions in a simple and natural way to provide a working model of externalities that can be applied to issues such as monopoly policy and labor market policies. Drawing on comparatively well understood models in cooperative game theory and the author's own research on mathematical models of biform games, this unique approach and treatment of game theory, updated and expanded to stay on the cutting edge, will be a useful resource for students and scholars of economics and public policy, as well as for policymakers themselves.

This book examines the economics of natural resource markets and pricing, as well as the field of natural resource economics in general. It presents the key contributions to this field of research, including the pioneering works and contemporary studies. The book highlights the basic principles and ideas underlying theoretical models of resource pricing. The models considered in the book underline the fundamental determinants of resource prices and the economic nature of rents for non-renewable and renewable resources. Besides the classical theory of exhaustible resource economics, the book includes several issues that are of high importance for global economic growth, such as the transition to alternative energy and the economics of climate change. The authors also consider the issues of commodity pricing and a resource cartel's activity that are relevant to the world oil market. The book provides analytical solutions illustrated with numerical examples. It allows an intuitive understanding of the subject and the model inferences through graphical illustrations and an informal introduction. It, therefore, is a must-read for everybody interested in a better understanding of resource prices, resource markets, and resource economics.

This book contains thirty-five selected papers presented at the International Conference on Evolutionary and Deterministic Methods for Design, Optimization and Control with Applications to Industrial and Societal Problems (EUROGEN 2017). This was one of the Thematic Conferences of the European Community on Computational Methods in Applied Sciences (ECCOMAS). Topics treated in the various chapters reflect the state of the art in theoretical and numerical methods and tools for optimization, and engineering design and societal applications. The volume focuses particularly on intelligent systems for multidisciplinary design optimization (mdo) problems based on multi-hybridized software, adjoint-based and one-shot methods, uncertainty quantification and optimization, multidisciplinary design optimization, applications of game theory to industrial optimization problems, applications in structural and civil engineering optimum design and surrogate models based optimization methods in aerodynamic design.

Written engagingly and with agreeable humour, this book balances a light touch with a rigorous yet economical account of the theory of games and bargaining models. It provides a precise interpretation, discussion and mathematical analysis for a wide range of game-like problems in economics, sociology, strategic studies and war.
There is first an informal introduction to game theory, which can be understood by non-mathematicians, which covers the basic ideas of extensive form, pure and mixed strategies and the minimax theorem. The general theory of non-cooperative games is then given a detailed mathematical treatment in the second chapter. Next follows a first class account of linear programming, theory and practice, terse, rigorous and readable, which is applied as a tool to matrix games and economics from duality theory via the equilibrium theorem, with detailed explanations of computational aspects of the simplex algorithm.
The remaining chapters give an unusually comprehensive but concise treatment of cooperative games, an original account of bargaining models, with a skillfully guided tour through the Shapley and Nash solutions for bimatrix games and a carefully illustrated account of finding the best threat strategies.
Balances a light touch with a rigorous yet economical account of the theory of games and bargaining modelsShows basic ideas of extensive form, pure and mixed strategies, the minimax theorem, non-cooperative and co-operative games, and a first class account of linear programming, theory and practiceBased on a series of lectures given by the author in the theory of games at Royal Holloway College"

This book introduces and analyses the latest maximum power point tracking (MPPT) techniques, which can effectively reduce the cost of power generated from photovoltaic energy systems. It also presents a detailed description, analysis, and comparison of various MPPT techniques applied to stand-alone systems and those interfaced with electric utilities, examining their performance under normal and abnormal operating conditions. These techniques, which and can be conventional or smart, are a current hot topic, and this book is a valuable reference resource for academic researchers and industry professionals who are interested in exploring and implementing advanced MPPT for photovoltaic systems. It is also useful for graduate students who are looking to expand their knowledge of MPPT techniques.

This book includes a collection of articles that present recent developments in the fields of optimization and dynamic game theory, economic dynamics, dynamic theory of the firm, and population dynamics and non standard applications of optimal control theory. The authors of the articles are well respected authorities in their fields and are known for their high quality research in the fields of optimization and economic dynamics.

This book introduces readers to the use of R codes for optimization problems. First, it provides the necessary background to understand data envelopment analysis (DEA), with a special emphasis on fuzzy DEA. It then describes DEA models, including fuzzy DEA models, and shows how to use them to solve optimization problems with R. Further, it discusses the main advantages of R in optimization problems, and provides R codes based on real-world data sets throughout. Offering a comprehensive review of DEA and fuzzy DEA models and the corresponding R codes, this practice-oriented reference guide is intended for masters and Ph.D. students in various disciplines, as well as practitioners and researchers.

This monograph presents new theories and methods for fixed-time cooperative control of multi-agent systems. Fundamental concepts of fixed-time stability and stabilization are introduced with insightful understanding. This book presents solutions for several problems of fixed-time cooperative control using systematic design methods. The book compares fixed-time cooperative control with asymptotic cooperative control, demonstrating how the former can achieve better closed-loop performance and disturbance rejection properties. It also discusses the differences from finite-time control, and shows how fixed-time cooperative control can produce the faster rate of convergence and provide an explicit estimate of the settling time independent of initial conditions. This monograph presents multiple applications of fixed-time control schemes, including to distributed optimization of multi-agent systems, making it useful to students, researchers and engineers alike.

This is the first book to comprehensively examine the asymptotic behavior of dynamic monopolies, duopolies, and oligopolies where firms face information and implementation delays. It considers discrete and continuous timescales, continuously distributed delays, as well as single and multiple delays. It also discusses models with linear and hyperbolic price functions in three types of oligopolies: Cournot competition with quantity-adjusting firms, Bertrand competition with price-adjusting firms, and mixed oligopolies with both types of firms. In addition to the traditional Cournot-Nash equilibria, it introduces cases of partial cooperation are also introduced, leading to the analysis of cartelizing groups of firms and possible governmental actions against antitrust behavior. Further, the book investigates special processes for firms learning about the uncertain price function based on repeated market information. It addresses asymptotic properties of the associated dynamic systems, derives stability conditions, identifies stability switching curves, and presents in global analyses of cases of instability. The book includes both theoretical results and computer studies to illustrate and verify the theoretical findings.

With the diversification of Internet services and the increase in mobile users, efficient management of network resources has become an extremely important issue in the field of wireless communication networks (WCNs). Adaptive resource management is an effective tool for improving the economic efficiency of WCN systems as well as network design and construction, especially in view of the surge in mobile device demands. This book presents modelling methods based on queueing theory and Markov processes for a wide variety of WCN systems, as well as precise and approximate analytical solution methods for the numerical evaluation of the system performance. This is the first book to provide an overview of the numerical analyses that can be gleaned by applying queueing theory, traffic theory and other analytical methods to various WCN systems. It also discusses the recent advances in the resource management of WCNs, such as broadband wireless access networks, cognitive radio networks, and green cloud computing. It assumes a basic understanding of computer networks and queueing theory, and familiarity with stochastic processes is also recommended. The analysis methods presented in this book are useful for first-year-graduate or senior computer science and communication engineering students. Providing information on network design and management, performance evaluation, queueing theory, game theory, intelligent optimization, and operations research for researchers and engineers, the book is also a valuable reference resource for students, analysts, managers and anyone in the industry interested in WCN system modelling, performance analysis and numerical evaluation.

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.

This volume collects contributions from the talks given at the Game Theory and Management Conference held in St. Petersburg, Russia, in June 2017. It covers a wide spectrum of topics, among which are: game theory and management applications in fields such as: strategic management, industrial organization, marketing, operations and supply chain management, public management, financial management, human resources, energy and resource management, and others; cooperative games; dynamic games; evolutionary games; stochastic games.