This book presents recent advances on the design of intelligent systems based on fuzzy logic, neural networks and nature-inspired optimization and their application in areas such as, intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems. The book is organized in eight main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of theoretical aspects of fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on fuzzy systems. The second part contains papers with the main theme of neural networks theory, which are basically papers dealing with new concepts and algorithms in neural networks. The third part contains papers describing applications of neural networks in diverse areas, such as time series prediction and pattern recognition. The fourth part contains papers describing new nature-inspired optimization algorithms. The fifth part presents diverse applications of nature-inspired optimization algorithms. The sixth part contains papers describing new optimization algorithms. The seventh part contains papers describing applications of fuzzy logic in diverse areas, such as time series prediction and pattern recognition. Finally, the eighth part contains papers that present enhancements to meta-heuristics based on fuzzy logic techniques.

This book presents the latest research findings and state-of-the-art solutions on optimization techniques and provides new research direction and developments. Both the theoretical and practical aspects of the book will be much beneficial to experts and students in optimization and operation research community. It selects high quality papers from The International Conference on Optimization: Techniques and Applications (ICOTA2013). The conference is an official conference series of POP (The Pacific Optimization Research Activity Group; there are over 500 active members). These state-of-the-art works in this book authored by recognized experts will make contributions to the development of optimization with its applications.

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 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.

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 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)."

This book bridges the widening gap between two crucial constituents of computational intelligence: the rapidly advancing technologies of machine learning in the digital information age, and the relatively slow-moving field of general-purpose search and optimization algorithms. With this in mind, the book serves to offer a data-driven view of optimization, through the framework of memetic computation (MC). The authors provide a summary of the complete timeline of research activities in MC - beginning with the initiation of memes as local search heuristics hybridized with evolutionary algorithms, to their modern interpretation as computationally encoded building blocks of problem-solving knowledge that can be learned from one task and adaptively transmitted to another. In the light of recent research advances, the authors emphasize the further development of MC as a simultaneous problem learning and optimization paradigm with the potential to showcase human-like problem-solving prowess; that is, by equipping optimization engines to acquire increasing levels of intelligence over time through embedded memes learned independently or via interactions. In other words, the adaptive utilization of available knowledge memes makes it possible for optimization engines to tailor custom search behaviors on the fly - thereby paving the way to general-purpose problem-solving ability (or artificial general intelligence). In this regard, the book explores some of the latest concepts from the optimization literature, including, the sequential transfer of knowledge across problems, multitasking, and large-scale (high dimensional) search, systematically discussing associated algorithmic developments that align with the general theme of memetics. The presented ideas are intended to be accessible to a wide audience of scientific researchers, engineers, students, and optimization practitioners who are familiar with the commonly used terminologies of evolutionary computation. A full appreciation of the mathematical formalizations and algorithmic contributions requires an elementary background in probability, statistics, and the concepts of machine learning. A prior knowledge of surrogate-assisted/Bayesian optimization techniques is useful, but not essential.

This book covers the latest advances in playful user interfaces - interfaces that invite social and physical interaction. These new developments include the use of audio, visual, tactile and physiological sensors to monitor, provide feedback and anticipate the behavior of human users. The decreasing cost of sensor and actuator technology makes it possible to integrate physical behavior information in human-computer interactions. This leads to many new entertainment and game applications that allow or require social and physical interaction in sensor- and actuator-equipped smart environments. The topics discussed include: human-nature interaction, human-animal interaction and the interaction with tangibles that are naturally integrated in our smart environments. Digitally supported remote audience participation in artistic or sport events is also discussed. One important theme that emerges throughout the book is the involvement of users in the digital-entertainment design process or even design and implementation of interactive entertainment by users themselves, including children doing so in educational settings.

This book covers various topics regarding the design of compliant mechanisms using topology optimization that have attracted a great deal of attention in recent decades. After comprehensively describing state-of-the-art methods for designing compliant mechanisms, it provides a new topology optimization method for finding new flexure hinges. It then presents several attempts to obtain distributed compliant mechanisms using the topology optimization method. Further, it discusses a Jacobian-based topology optimization method for compliant parallel mechanisms, and introduces readers to the topology optimization of compliant mechanisms, taking into account geometrical nonlinearity and reliability. Providing a systematic method for topology optimization of flexure hinges, which are essential for designing compliant mechanisms, the book offers a valuable resource for all readers who are interested in designing compliant mechanism-based positioning stages. In addition, the methods for solving the de facto hinges in topology optimized compliant mechanisms will benefit all engineers seeking to design micro-electro-mechanical system (MEMS) structures.

This book provides a comprehensive and practically minded introduction into serious games for law enforcement agencies. Serious games offer wide ranging benefits for law enforcement with applications from professional trainings to command-level decision making to the preparation for crises events. This book explains the conceptual foundations of virtual and augmented reality, gamification and simulation. It further offers practical guidance on the process of serious games development from user requirements elicitation to evaluation. The chapters are intended to provide principles, as well as hands-on knowledge to plan, design, test and apply serious games successfully in a law enforcement environment. A diverse set of case studies showcases the enormous variety that is possible in serious game designs and application areas and offers insights into concrete design decisions, design processes, benefits and challenges. The book is meant for law enforcement professionals interested in commissioning their own serious games as well as game designers interested in collaborative pedagogy and serious games for the law enforcement and security sector.

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."

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.

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.

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 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.

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. "

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.

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."

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.

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.

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.

This book opens new avenues in understanding mathematical models within the context of a transition economy. The exposition lays out the methods for combining different mathematical structures and tools to effectively build the next model that will accurately reflect real world economic processes. Mathematical modeling of weather phenomena allows us to forecast certain essential weather parameters without any possibility of changing them. By contrast, modeling of transition economies gives us the freedom to not only predict changes in important indexes of all types of economies, but also to influence them more effectively in the desired direction. Simply put: any economy, including a transitional one, can be controlled. This book is useful to anyone who wants to increase profits within their business, or improve the quality of their family life and the economic area they live in. It is beneficial for undergraduate and graduate students specializing in the fields of Economic Informatics, Economic Cybernetics, Applied Mathematics and Large Information Systems, as well as for professional economists, and employees of state planning and statistical organizations.

In the paper we propose a model of tax incentives optimization for inve- ment projects with a help of the mechanism of accelerated depreciation. Unlike the tax holidays which influence on effective income tax rate, accelerated - preciation affects on taxable income. In modern economic practice the state actively use for an attraction of - vestment into the creation of new enterprises such mechanisms as accelerated depreciation and tax holidays. The problem under our consideration is the following. Assume that the state (region) is interested in realization of a certain investment project, for ex- ple, the creation of a new enterprise. In order to attract a potential investor the state decides to use a mechanism of accelerated tax depreciation. The foll- ing question arise. What is a reasonable principle for choosing depreciation rate? From the state's point of view the future investor's behavior will be rat- nal. It means that while looking at economic environment the investor choose such a moment for investment which maximizes his expected net present value (NPV) from the given project. For this case both criteria and "investment rule" depend on proposed (by the state) depreciation policy. For the simplicity we will suppose that the purpose of the state for a given project is a maximi- tion of a discounted tax payments into the budget from the enterprise after its creation. Of course, these payments depend on the moment of investor's entry and, therefore, on the depreciation policy established by the state.

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

Along with the traditional material concerning linear programming (the simplex method, the theory of duality, the dual simplex method), In-Depth Analysis of Linear Programming contains new results of research carried out by the authors. For the first time, the criteria of stability (in the geometrical and algebraic forms) of the general linear programming problem are formulated and proved. New regularization methods based on the idea of extension of an admissible set are proposed for solving unstable (ill-posed) linear programming problems. In contrast to the well-known regularization methods, in the methods proposed in this book the initial unstable problem is replaced by a new stable auxiliary problem. This is also a linear programming problem, which can be solved by standard finite methods. In addition, the authors indicate the conditions imposed on the parameters of the auxiliary problem which guarantee its stability, and this circumstance advantageously distinguishes the regularization methods proposed in this book from the existing methods. In these existing methods, the stability of the auxiliary problem is usually only presupposed but is not explicitly investigated. In this book, the traditional material contained in the first three chapters is expounded in much simpler terms than in the majority of books on linear programming, which makes it accessible to beginners as well as those more familiar with the area.