The era of interior point methods (IPMs) was initiated by N. Karmarkar's 1984 paper, which triggered turbulent research and reshaped almost all areas of optimization theory and computational practice. This book offers comprehensive coverage of IPMs. It details the main results of more than a decade of IPM research. Numerous exercises are provided to aid in understanding the material.

This book focuses on various aspects of dynamic game theory, presenting state-of-the-art research and serving as a testament to the vitality and growth of the field of dynamic games and their applications. Its contributions, written by experts in their respective disciplines, are outgrowths of presentations originally given at the 14th International Symposium of Dynamic Games and Applications held in Banff.

"Advances in Dynamic Games" covers a variety of topics, ranging from evolutionary games, theoretical developments in game theory and algorithmic methods to applications, examples, and analysis in fields as varied as mathematical biology, environmental management, finance and economics, engineering, guidance and control, and social interaction. Featured throughout are valuable tools and resources for researchers, practitioners, and graduate students interested in dynamic games and their applications to mathematics, engineering, economics, and management science. "

New Approaches to Circle Packing into the Square is devoted to the most recent results on the densest packing of equal circles in a square. In the last few decades, many articles have considered this question, which has been an object of interest since it is a hard challenge both in discrete geometry and in mathematical programming. The authors have studied this geometrical optimization problem for a long time, and they developed several new algorithms to solve it. The book completely covers the investigations on this topic.

Like norms, translation invariant functions are a natural and powerful tool for the separation of sets and scalarization. This book provides an extensive foundation for their application. It presents in a unified way new results as well as results which are scattered throughout the literature. The functions are defined on linear spaces and can be applied to nonconvex problems. Fundamental theorems for the function class are proved, with implications for arbitrary extended real-valued functions. The scope of applications is illustrated by chapters related to vector optimization, set-valued optimization, and optimization under uncertainty, by fundamental statements in nonlinear functional analysis and by examples from mathematical finance as well as from consumer and production theory. The book is written for students and researchers in mathematics and mathematical economics. Engineers and researchers from other disciplines can benefit from the applications, for example from scalarization methods for multiobjective optimization and optimal control problems.

Computational optimization is an important paradigm with a wide range of applications. In virtually all branches of engineering and industry, we almost always try to optimize something - whether to minimize the cost and energy consumption, or to maximize profits, outputs, performance and efficiency. In many cases, this search for optimality is challenging, either because of the high computational cost of evaluating objectives and constraints, or because of the nonlinearity, multimodality, discontinuity and uncertainty of the problem functions in the real-world systems. Another complication is that most problems are often NP-hard, that is, the solution time for finding the optimum increases exponentially with the problem size. The development of efficient algorithms and specialized techniques that address these difficulties is of primary importance for contemporary engineering, science and industry. This book consists of 12 self-contained chapters, contributed from worldwide experts who are working in these exciting areas. The book strives to review and discuss the latest developments concerning optimization and modelling with a focus on methods and algorithms for computational optimization. It also covers well-chosen, real-world applications in science, engineering and industry. Main topics include derivative-free optimization, multi-objective evolutionary algorithms, surrogate-based methods, maximum simulated likelihood estimation, support vector machines, and metaheuristic algorithms. Application case studies include aerodynamic shape optimization, microwave engineering, black-box optimization, classification, economics, inventory optimization and structural optimization. This graduate level book can serve as an excellent reference for lecturers, researchers and students in computational science, engineering and industry.

The second edition of this textbook presents the basic mathematical knowledge and skills that are needed for courses on modern theoretical physics, such as those on quantum mechanics, classical and quantum field theory, and related areas. The authors stress that learning mathematical physics is not a passive process and include numerous detailed proofs, examples, and over 200 exercises, as well as hints linking mathematical concepts and results to the relevant physical concepts and theories. All of the material from the first edition has been updated, and five new chapters have been added on such topics as distributions, Hilbert space operators, and variational methods. The text is divided into three parts: - Part I: A brief introduction to (Schwartz) distribution theory. Elements from the theories of ultra distributions and (Fourier) hyperfunctions are given in addition to some deeper results for Schwartz distributions, thus providing a rather comprehensive introduction to the theory of generalized functions. Basic properties and methods for distributions are developed with applications to constant coefficient ODEs and PDEs. The relation between distributions and holomorphic functions is considered, as well as basic properties of Sobolev spaces. - Part II: Fundamental facts about Hilbert spaces. The basic theory of linear (bounded and unbounded) operators in Hilbert spaces and special classes of linear operators - compact, Hilbert-Schmidt, trace class, and Schroedinger operators, as needed in quantum physics and quantum information theory - are explored. This section also contains a detailed spectral analysis of all major classes of linear operators, including completeness of generalized eigenfunctions, as well as of (completely) positive mappings, in particular quantum operations. - Part III: Direct methods of the calculus of variations and their applications to boundary- and eigenvalue-problems for linear and nonlinear partial differential operators. The authors conclude with a discussion of the Hohenberg-Kohn variational principle. The appendices contain proofs of more general and deeper results, including completions, basic facts about metrizable Hausdorff locally convex topological vector spaces, Baire's fundamental results and their main consequences, and bilinear functionals. Mathematical Methods in Physics is aimed at a broad community of graduate students in mathematics, mathematical physics, quantum information theory, physics and engineering, as well as researchers in these disciplines. Expanded content and relevant updates will make this new edition a valuable resource for those working in these disciplines.

This book focuses on the latest advances in nonlinear dynamic modeling in economics and finance, mainly-but not solely-based on the description of strategic interaction by using concepts and methods from dynamic and evolutionary game theory. The respective chapters cover a range of theoretical issues and examples concerning how the qualitative theory of dynamical systems is used to analyze the local and global bifurcations that characterize complex behaviors observed in social systems where heterogeneous and boundedly rational economic agents interact. Nonlinear dynamical systems, represented by difference and differential and functional equations, are extensively used to simulate the behavior of time-evolving economic systems, also in the presence of time lags, discontinuities, and hysteresis phenomena. In addition, some theoretical issues and particular applications are discussed, as well. The contributions gathered here offer an up-to-date review of the latest research in this rapidly developing research area.

Structural Optimization is intended to supplement the engineer s box of analysis and design tools making optimization as commonplace as the finite element method in the engineering workplace. It begins with an introduction to structural optimization and the methods of nonlinear programming such as Lagrange multipliers, Kuhn-Tucker conditions, and calculus of variations. It then discusses solution methods for optimization problems such as the classic method of linear programming which leads to the method of sequential linear programming. It then proposes using sequential linear programming together with the incremental equations of structures as a general method for structural optimization. It is furthermore intended to give the engineer an overview of the field of structural optimization."

This book presents open optimization problems in graph theory and networks. Each chapter reflects developments in theory and applications based on Gregory Gutin's fundamental contributions to advanced methods and techniques in combinatorial optimization. Researchers, students, and engineers in computer science, big data, applied mathematics, operations research, algorithm design, artificial intelligence, software engineering, data analysis, industrial and systems engineering will benefit from the state-of-the-art results presented in modern graph theory and its applications to the design of efficient algorithms for optimization problems. Topics covered in this work include: * Algorithmic aspects of problems with disjoint cycles in graphs * Graphs where maximal cliques and stable sets intersect * The maximum independent set problem with special classes * A general technique for heuristic algorithms for optimization problems * The network design problem with cut constraints * Algorithms for computing the frustration index of a signed graph * A heuristic approach for studying the patrol problem on a graph * Minimum possible sum and product of the proper connection number * Structural and algorithmic results on branchings in digraphs * Improved upper bounds for Korkel--Ghosh benchmark SPLP instances

The book presents a unified treatment of integer programming and network models with topics ranging from exact and heuristic algorithms to network flows, traveling salesman tours, and traffic assignment problems. While the emphasis of the book is on models and applications, the most important methods and algorithms are described in detail and illustrated by numerical examples. The formulations and the discussion of a large variety of models provides insight into their structures that allows the user to better evaluate the solutions to the problems.

Complex Social Networks is a newly emerging (hot) topic with applications in a variety of domains, such as communication networks, engineering networks, social networks, and biological networks. In the last decade, there has been an explosive growth of research on complex real-world networks, a theme that is becoming pervasive in many disciplines, ranging from mathematics and computer science to the social and biological sciences. Optimization of complex communication networks requires a deep understanding of the interplay between the dynamics of the physical network and the information dynamics within the network. Although there are a few books addressing social networks or complex networks, none of them has specially focused on the optimization perspective of studying these networks. This book provides the basic theory of complex networks with several new mathematical approaches and optimization techniques to design and analyze dynamic complex networks. A wide range of applications and optimization problems derived from research areas such as cellular and molecular chemistry, operations research, brain physiology, epidemiology, and ecology.

This contributed volume contains fourteen papers based on selected presentations from the European Conference on Game Theory SING11-GTM 2015, held at Saint Petersburg State University in July 2015, and the Networking Games and Management workshop, held at the Karelian Research Centre of the Russian Academy of Sciences in Petrozvavodsk, Russia, also in July 2015. These papers cover a wide range of topics in game theory, including recent advances in areas with high potential for future work, as well as new developments on classical results. Some of these include A new approach to journal ranking using methods from social choice theory; A differential game of a duopoly in which two firms are competing for market share in an industry with network externalities; The impact of information propagation in the model of tax audits; A voting model in which the results of previous votes can affect the process of coalition formation in a decision-making body; The Selten-Szidarovsky technique for the analysis of Nash equilibria of games with an aggregative structure; Generalized nucleoli and generalized bargaining sets for games with restricted cooperation; Bayesian networks and games of deterrence; and A new look at the study of solutions for games in partition function form. The maturity and vitality of modern-day game theory are reflected in the new ideas, novel applications, and contributions of young researchers represented in this collection. It will be of interest to anyone doing theoretical research in game theory or working on one its numerous applications.

This chapter is organized as follows. The economic problem on which this book focuses is motivated in Section 1. The two tools used to study this economic problem, which are real options theory and game theory, are discussed in Sections 2 and 3, respectively. Section 4 surveys the contents of this book. In Section 5 some promising extensions of the research presented in this book are listed. 1. TECHNOLOGY INVESTMENT Investment expenditures of companies govern economic growth. Es pecially investments in new and more efficient technologies are an impor tant determinant. In particular, in the last two decades an increasing part of the investment expenditures concerns investments in informa tion and communication technology. Kriebel, 1989 notes that (already) in 1989 roughly 50 percent of new corporate capital expenditures by major United States companies was in information and communication technology. Due to the rapid progress in these technologies, the tech nology investment decision of the individual firm has become a very complex matter. As an example of the very high pace of technological improvement consider the market for personal computers. IBM intro duced its Pentium personal computers in the early 1990s at the same price at which it introduced its 80286 personal computers in the 1980s. Therefore it took less than a decade to improve on the order of twenty times in terms of both speed and memory capacities, without increasing the cost (Yorukoglu, 1998)."

For both public and private managers, the book Optimization Methods for a Stakeholder Society is today's key to answer the problem of a sustainable development world. This world has to take into account the meaning of all stakeholders involved and has to reconcile a number of objectives, such as economic growth, employment and preservation of the ecosystem. Traditional methods, such as cost-benefit, are outmoded as they translate all these objectives into monetary costs, a materialistic approach. On the contrary, objectives have rather to stick to their own units, eventually indicators.
The author is in favor of the use of nonlinear methods in multi-objective optimization. Therefore, several nonlinear approaches are proposed, illustrated with many applications from different fields such as: privatization in the public sector, regional versus national economic policy in a country, location of a seaport, arms procurement, industrialization of a developing country, updating or replacement of old industry, pre- and post-evaluation of projects, performance management, marketing and distribution.

Though the game-theoretic approach has been vastly studied and utilized in relation to economics of industrial organizations, it has hardly been used to tackle safety management in multi-plant chemical industrial settings. Using Game Theory for Improving Safety within Chemical Industrial Parks presents an in-depth discussion of game-theoretic modeling which may be applied to improve cross-company prevention and -safety management in a chemical industrial park. By systematically analyzing game-theoretic models and approaches in relation to managing safety in chemical industrial parks, Using Game Theory for Improving Safety within Chemical Industrial Parks explores the ways game theory can predict the outcome of complex strategic investment decision making processes involving several adjacent chemical plants. A number of game-theoretic decision models are discussed to provide strategic tools for decision-making situations. Offering clear and straightforward explanations of methodologies, Using Game Theory for Improving Safety within Chemical Industrial Parks provides managers and management teams with approaches to asses situations and to improve strategic safety- and prevention arrangements.

Dynamic game theory serves the purpose of including strategic interaction in decision making and is therefore often applied to economic problems. This book presents the state-of-the-art and directions for future research in dynamic game theory related to economics. It was initiated by contributors to the 12th Viennese Workshop on Optimal Control, Dynamic Games and Nonlinear Dynamics and combines a selection of papers from the workshop with invited papers of high quality.

Everything should be made as simple as possible, but not simpler. (Albert Einstein, Readers Digest, 1977) The modern practice of creating technical systems and technological processes of high effi.ciency besides the employment of new principles, new materials, new physical effects and other new solutions ( which is very traditional and plays the key role in the selection of the general structure of the object to be designed) also includes the choice of the best combination for the set of parameters (geometrical sizes, electrical and strength characteristics, etc.) concretizing this general structure, because the Variation of these parameters ( with the structure or linkage being already set defined) can essentially affect the objective performance indexes. The mathematical tools for choosing these best combinations are exactly what is this book about. With the advent of computers and the computer-aided design the pro bations of the selected variants are usually performed not for the real examples ( this may require some very expensive building of sample op tions and of the special installations to test them ), but by the analysis of the corresponding mathematical models. The sophistication of the mathematical models for the objects to be designed, which is the natu ral consequence of the raising complexity of these objects, greatly com plicates the objective performance analysis. Today, the main (and very often the only) available instrument for such an analysis is computer aided simulation of an object's behavior, based on numerical experiments with its mathematical model."

This book has its focus on the dynamics of oligopoly games. Several contributions show how easily the unique Nash equilibria in some most traditional oligopoly models may lose stability, giving way to complex phenomena, such as periodic/chaotic processes, and to multi stability of coexistent attractors. The bifurcations producing these phenomena are studied by means of recently accumulated global methods, based on the use of critical curves. These tools are explained in a separate methodological chapter. The book also contains some historical background of the present theory. In this way the book becomes suitable also as an advanced text for industrial organisation courses. The various models presented in the book focus both classical Cournot types, and Hotelling`s "ice cream vendor" problems, including location choice. The author list comprises some of the most prolific contributors to current dynamic oligopoly modelling.

Today, the optimization of production planning processes by means of IT and quantitative methods is a de-facto standard in the energy industry. Franch et al. inChapter1andIkenouyeinChapter2giveanintroduction, overview, and reasonsforthis. Furthermore, theenergyproblemnowisnotonlyachallenging one but also one of the most important issues in the world from the political and economical points of view. In every country, the government is faced with the problem of how to adopt the system of 'Cap and Trade. ' Especially energy consuming industries, such as steel, power, oil and chemicals, are seriously confronted with this problem. VIII Preface This is also the reason why the German Operations Research Society (GOR) and one of its working groups, held a symposium with the title "Stochastic Optimization in the Energy Industry. " During the 78th meeting of the GOR working group "Praxis der Mathematischen Optimierung/Real World Optimization" in Aachen at Procom GmbH on April 21/22, 2007, the speakers with an application background explained their requirements for stochasticoptimizationsolutionsbasedonpracticalexperiences. Thespeakers from the research side and the software system suppliers examined di?erent aspects of the whole subject - from the integration of wind energy, the chain of errors in nuclear power plants and the scheduling of hydroelectric power stations, and the risk assessment in trading activities to the various software systems which support stochastic optimization methods. The symposium o?ered an interesting overview which re?ected the - quirements, possibilities and restrictions of "Stochastic Optimization in the Energy Industry.

This present book provides an alternative approach to study the pre-kernel solution of transferable utility games based on a generalized conjugation theory from convex analysis. Although the pre-kernel solution possesses an appealing axiomatic foundation that lets one consider this solution concept as a standard of fairness, the pre-kernel and its related solutions are regarded as obscure and too technically complex to be treated as a real alternative to the Shapley value. Comprehensible and efficient computability is widely regarded as a desirable feature to qualify a solution concept apart from its axiomatic foundation as a standard of fairness. We review and then improve an approach to compute the pre-kernel of a cooperative game by the indirect function. The indirect function is known as the Fenchel-Moreau conjugation of the characteristic function. Extending the approach with the indirect function, we are able to characterize the pre-kernel of the grand coalition simply by the solution sets of a family of quadratic objective functions.

This book presents comprehensive state-of-the-art theoretical analysis of the fundamental Newtonian and Newtonian-related approaches to solving optimization and variational problems. A central focus is the relationship between the basic Newton scheme for a given problem and algorithms that also enjoy fast local convergence. The authors develop general perturbed Newtonian frameworks that preserve fast convergence and consider specific algorithms as particular cases within those frameworks, i.e., as perturbations of the associated basic Newton iterations. This approach yields a set of tools for the unified treatment of various algorithms, including some not of the Newton type per se. Among the new subjects addressed is the class of degenerate problems. In particular, the phenomenon of attraction of Newton iterates to critical Lagrange multipliers and its consequences as well as stabilized Newton methods for variational problems and stabilized sequential quadratic programming for optimization. This volume will be useful to researchers and graduate students in the fields of optimization and variational analysis.

This is the fourth edition of a book that, after circulating in the form of l- ture notes at the universities of Rome (now La Sapienza University of Rome) and Siena in the late 1960s, was originally published in 1971 under the titleMat- maticalMethodsandModelsinEconomicDynamics. Inthosefortyoddyearstwo main developments have occurred in economic dynamics. The ?rst is the much greater amount of advanced mathematics that is being used today with respect to the past. The second is the increasing importance of non-linear modelling as contrastedwiththelinearapproach(which, however, hasnotgoneoutoffashion). This fourth edition re?ects both developments. It contains additional advanced mathematical tools, and a larger amount of non-linear mathematics and appli- tions. These developments are re?ected especially in Part III, that now accounts forwellover50%ofthebook. ItgoeswithoutsayingthatIhavemadeeverye?ort topreservetheuser-friendlyfeatureofthepreviouseditions: thespiritofthebook hasremainedthesame, namelytogiveacomprehensive, butsimple, treatmentof the mathematical methods commonly used in dynamical economics, and to show how they are applied to build and analyse economic models. Accordingly, the focus is on methods, and every mathematical technique - troduced is followed by its application to selected economic models that serve as examples. Theunifyingprincipleintheexpositionofthedi?erenteconomicm- els is then seen to be the common mathematical technique. This process will enable the readers not only to understand the basic literature, but also to build and analyse their own model

The International Conference on Health Care Systems Engineering (HCSE) provided a timely opportunity to discuss statistical analysis and operations management issues in health care delivery systems. The conference took place in Milan between May 22nd and 24th, 2013. Scientists and practitioners discussed new ideas, methods and technologies for improving the operation of health care organizations. The event and this resulting volume emphasize research in the field of health care systems engineering developed in close collaboration with clinicians. Topics applicable to researchers and practitioners include: hospital drug logistics, operating theatres, modelling and simulation in patient care and healthcare organizations, home care services.

Extending the well-known connection between classical linear potential theory and probability theory (through the interplay between harmonic functions and martingales) to the nonlinear case of tug-of-war games and their related partial differential equations, this unique book collects several results in this direction and puts them in an elementary perspective in a lucid and self-contained fashion.

The game-theoretic modelling of negotiations has been an active research area for the past five decades, that started with the seminal work by Nobel laureate John Nash in the early 1950s. This book provides a survey of some of the major developments in the field of strategic bargaining models with an emphasize on the role of threats in the negotiation process. Threats are all actions outside the negotiation room that negotiators have ate their disposal and the use of these actions affect the bargaining position of all negotiators. Of course, each negotiator aims to strengthen his own position. Examples of threats are the announcement of a strike by a union in centralized wage bargaining, or a nation's announcement of a trade war directed against other nations in negotiations for trade liberalization. This book is organized on the basis of a simple guiding principle: The situation in which none of the parties involved in the negotiations has threats at its disposal is the natural benchmark for negotiations where the parties can make threats. Also on the technical level, negotiations with variable threats build on and extend the techniques applied in analyzing bargaining situations without threats. The first part of this book, containing chapter 3-6, presents the no-threat case, and the second part, containing chapter 7-10, extends the analysis for negotiation situations where threats are present. A consistent and unifying framework is provided first in 2.