Sobolev spaces become the established and universal language of partial differential equations and mathematical analysis. Among a huge variety of problems where Sobolev spaces are used, the following important topics are the focus of this volume: boundary value problems in domains with singularities, higher order partial differential equations, local polynomial approximations, inequalities in Sobolev-Lorentz spaces, function spaces in cellular domains, the spectrum of a Schrodinger operator with negative potential and other spectral problems, criteria for the complete integration of systems of differential equations with applications to differential geometry, some aspects of differential forms on Riemannian manifolds related to Sobolev inequalities, Brownian motion on a Cartan-Hadamard manifold, etc.

Two short biographical articles on the works of Sobolev in the 1930s and the foundation of Akademgorodok in Siberia, supplied with unique archive photos of S. Sobolev are included.

This book develops models, results and algorithms for optimizing public transportation from a customer-oriented viewpoint. The methods used are based on graph-theoretic approaches and integer programming. The specific topics are all motivated by real-world examples which occurred in practical projects: location of stops, management of delay, and tariff zone design. An appendix summarizes some of the basics of optimization needed to interpret the material in the book.

Victor Isakov This volume contains various results on partial di?erential equations where Sobolev spaces are used. Their selection is motivated by the research int- ests of the editor and the geographicallinks to the places where S. L. Sobolev worked and lived: St. Petersburg, Moscow, and Novosibirsk. Most of the papers are written by leading experts in control theory and inverse pr- lems. Another reason for the selection is a strong link to applied areas. In my opinion, control theory and inverse problems are main areas of di?er- tial equations of importance for some branches of contemporary science and engineering. S. L. Sobolev, as many great mathematicians, was very much motivated by applications. He did not distinguished between pure and - plied mathematics, but, in his own words, between "good mathematics and bad mathematics. " While he possessed a brilliant analytical technique, he most valued innovative ideas, solutions of deep conceptual problems, and not mathematical decorations, perfecting exposition, and "generalizations. " S. L. Sobolev himself never published papers on inverse problems or c- trol theory, but he was very much aware of the state of art and he monitored research on inverse problems. In particular, in his lecture at a Conference on Di?erentialEquationsin1954(found inSobolev'sarchiveandmadeavailable to me by Alexander Bukhgeim), he outlined main inverse problems in g- physics: theinverseseismicproblem, theelectromagneticprospecting, andthe inverse problem of gravimetry.

This book provides successful implementations of metaheuristic methods for neural network training. It is the first book to achieve this objective. Moreover, the basic principles and fundamental ideas given in the book will allow the readers to create successful training methods on their own. Overall, the book's aim is to provide a broad coverage of the concepts, methods, and tools of the important area of ANNs within the realm of continuous optimization.

The primary objective underlying the Handbook on Modelling for Discrete Optimization is to demonstrate and detail the pervasive nature of Discrete Optimization. While its applications cut across an incredibly wide range of activities, many of the applications are only known to specialists. It is the aim of this handbook to correct this.

It has long been recognized that "modelling" is a critically important mathematical activity in designing algorithms for solving these discrete optimization problems. Nevertheless solving the resultant models is also often far from straightforward. In recent years it has become possible to solve many large-scale discrete optimization problems. However, some problems remain a challenge, even though advances in mathematical methods, hardware, and software technology have pushed the frontiers forward. This handbook couples the difficult, critical-thinking aspects of mathematical modelling with the hot area of discrete optimization. It will be done in an academic handbook treatment outlining the state-of-the-art for researchers across the domains of the Computer Science, Math Programming, Applied Mathematics, Engineering, and Operations Research. Included in the handbook's treatment are results from Graph Theory, Logic, Computer Science, and Combinatorics.

The chapters of this book are divided into two parts: (1) one dealing with general methods in the modelling of discrete optimization problems and (2) the other with specific applications. The first chapter of this volume, written by H. Paul Williams, can be regarded as a basic introduction of how to model discrete optimization problems as mixed integer problems, and outlines the main methods of solving them. In the second part of the book various real life applications are presented, most of them formulated as mixed integer linear or nonlinear programming problems. These applications include network problems, constant logic problems, many engineering problems, computer design, finance problems, medical diagnosis and medical treatment problems, applications of the Genome project, an array of transportation scheduling problems, and other applications.

Further information including a detailed Table of Contents and Preface can be found and examined on the Handbook's web page at http: //www.springer.com/0-387-32941-2.

Written by a world leader in the field and aimed at researchers in applied and engineering sciences, this brilliant text has as its main goal imparting an understanding of the methods so that practitioners can make immediate use of existing algorithms and software, and so that researchers can extend the state of the art and find new applications. It includes algorithms on seeking feasibility and analyzing infeasibility, as well as describing new and surprising applications.

This volume presents a wide range of medical applications that can utilize mathematical computing. This work grew out of a workshop on optimization which was held during the 2005 CIM Thematic Term on Optimization in Coimbra, Portugal. It provides an overview of the state-of-the-art in optimization in medicine and will serve as an excellent reference for researchers in the medical computing community and for those working in applied mathematics and optimization.

A combination of both Integer Programming and Nonlinear Optimization, this is a powerful book that surveys the field and provides a state-of-the-art treatment of Nonlinear Integer Programming. It is the first book available on the subject. The book aims to bring the theoretical foundation and solution methods for nonlinear integer programming to students and researchers in optimization, operations research, and computer science.

This monograph is devoted to recent progress in the turnpike t- ory. Turnpike properties are well known in mathematical economics. The term was ?rst coined by Samuelson who showed that an e?cient expanding economy would for most of the time be in the vicinity of a balanced equilibrium path (also called a von Neumann path) [78, 79]. These properties were studied by many authors for optimal trajec- ries of a Neumann-Gale model determined by a superlinear set-valued mapping. In the monograph we discuss a number of results conce- ing turnpike properties in the calculus of variations and optimal control which were obtained by the author in the last ten years. These results showthattheturnpikepropertiesareageneralphenomenonwhichholds for various classes of variational problems and optimal control problems. Turnpike properties are studied for optimal control problems on- nite time intervals [T ,T ] of the real line. Solutions of such problems 1 2 (trajectories) always depend on the time interval [T ,T ], an optimality 1 2 criterion which is usually determined by a cost function, and on data which is some initial conditions. In the turnpike theory we are int- ested in the structure of solutions of optimal problems. We study the behavior of solutions when an optimality criterion is ?xed while T ,T 1 2 andthedatavary.

This is a comprehensive overview of the basics of fuzzy control, which also brings together some recent research results in soft computing, in particular fuzzy logic using genetic algorithms and neural networks.

This book offers researchers not only a solid background but also a snapshot of the current state of the art in this field.

This volume consists of papers presented in the special sessions on "Complex and Numerical Analysis," "Value Distribution Theory and Complex Domains," and "Use of Symbolic Computation in Mathematics Education" of the ISAAC'97 Congress held at the University of Delaware, during June 2-7, 1997. The ISAAC Congress coincided with a U.S.-Japan Seminar also held at the University of Delaware. The latter was supported by the National Science Foundation through Grant INT-9603029 and the Japan Society for the Promotion of Science through Grant MTCS-134. It was natural that the participants of both meetings should interact and consequently several persons attending the Congress also presented papers in the Seminar. The success of the ISAAC Congress and the U.S.-Japan Seminar has led to the ISAAC'99 Congress being held in Fukuoka, Japan during August 1999. Many of the same participants will return to this Seminar. Indeed, it appears that the spirit of the U.S.-Japan Seminar will be continued every second year as part of the ISAAC Congresses. We decided to include with the papers presented in the ISAAC Congress and the U.S.-Japan Seminar several very good papers by colleagues from the former Soviet Union. These participants in the ISAAC Congress attended at their own expense.

In the fifties and sixties, several real problems, old and new, especially in Physics, Mechanics, Fluidodynamics, Structural Engi- neering, have shown the need of new mathematical models for study- ing the equilibrium of a system. This has led to the formulation of Variational Inequalities (by G. Stampacchia), and to the develop- ment of Complementarity Systems (by W.S. Dorn, G.B. Dantzig, R.W. Cottle, O.L. Mangasarian et al.) with important applications in the elasto-plastic field (initiated by G. Maier). The great advan- tage of these models is that the equilibrium is not necessarily the extremum of functional, like energy, so that no such functional must be supposed to exist. In the same decades, in some fields like Control Theory, Net- works, Industrial Systems, Logistics, Management Science, there has been a strong request of mathmatical models for optimizing situa- tions where there are concurrent objectives, so that Vector Optimiza- tion (initiated by W. Pareto) has received new impetus. With regard to equilibrium problems, Vector Optimization has the above - mentioned drawback of being obliged to assume the exis- tence of a (vector) functional. Therefore, at the end of the seventies the study of Vector Variational Inequalities began with the scope of exploiting the advantages of both variational and vector models. This volume puts together most of the recent mathematical results in Vector Variational Inequalities with the purpose of contributing to further research.

The purpose of this book is to acquaint the reader with the developments in bilinear systems theory and its applications. Bilinear systems can be used to represent a wide range of physical, chemical, biological, and social systems, as well as manufacturing processes, which cannot be effectively modeled under the assumption of linearity. This book provides a unified approach for the identification and control of nonlinear complex objects that can be transformed into bilinear systems, with a focus on the control of open physical processes functioning in a non-equilibrium mode.

The material is intended for graduate students, researchers, and specialists engaged in the fields of quantum and molecular computing, control of physical processes, biophysics, superconducting magnetism, physical information science, mathematics, and engineering.

This book is devoted to a new branch of experimental design theory called simulation experimental design. There are many books devoted either to the theory of experimental design or to system simulation techniques, but in this book an approach to combine both fields is developed. Especially the mathematical theory of such universal variance reduction techniques as splitting and Russian Roulette is explored. The book contains a number of results on regression design theory related to nonlinear problems, the E-optimum criterion and designs which minimize bias. Audience: This volume will be of value to readers interested in systems simulation, applied statistics and numerical methods with basic knowledge of applied statistics and linear algebra.

This monograph provides an introduction to the theory of topologies defined on the closed subsets of a metric space, and on the closed convex subsets of a normed linear space as well. A unifying theme is the relationship between topology and set convergence on the one hand, and set functionals on the other. The text includes for the first time anywhere an exposition of three topologies that over the past ten years have become fundamental tools in optimization, one-sided analysis, convex analysis, and the theory of multifunctions: the Wijsman topology, the Attouch--Wets topology, and the slice topology. Particular attention is given to topologies on lower semicontinuous functions, especially lower semicontinuous convex functions, as associated with their epigraphs. The interplay between convex duality and topology is carefully considered and a chapter on set-valued functions is included. The book contains over 350 exercises and is suitable as a graduate text. This book is of interest to those working in general topology, set-valued analysis, geometric functional analysis, optimization, convex analysis and mathematical economics.

Graph theory is very much tied to the geometric properties of optimization and combinatorial optimization. Moreover, graph theory's geometric properties are at the core of many research interests in operations research and applied mathematics. Its techniques have been used in solving many classical problems including maximum flow problems, independent set problems, and the traveling salesman problem.

Graph Theory and Combinatorial Optimization explores the field's classical foundations and its developing theories, ideas and applications to new problems. The book examines the geometric properties of graph theory and its widening uses in combinatorial optimization theory and application. The field's leading researchers have contributed chapters in their areas of expertise.

In a relatively short period of time, data envelopment analysis (DEA) has grown into a powerful analytical tool for measuring and evaluating performance. DEA is computational at its core and this book is one of several Springer aim to publish on the subject. This work deals with the micro aspects of handling and modeling data issues in DEA problems. It is a handbook treatment dealing with specific data problems, including imprecise data and undesirable outputs.

This book proposes a unified algorithmic framework based on dual optimization techniques that have complexities that are linear in the number of subcarriers and users, and that achieve negligible optimality gaps in standards-based numerical simulations. Adaptive algorithms based on stochastic approximation techniques are also proposed, which are shown to achieve similar performance with even much lower complexity. All the algorithms proposed are clearly presented in concise block diagrams allowing the reader to implement these algorithms in the software of their choice. This book is an accessible reference for researchers and industry practitioners alike.

The complexity of issues requiring rational decision making grows and thus such decisions are becoming more and more difficult, despite advances in methodology and tools for decision support and in other areas of research. Globalization, interlinks between environmental, industrial, social and political issues, and rapid speed of change all contribute to the increase of this complexity. Specialized knowledge about decision-making processes and their support is increasing, but a large spectrum of approaches presented in the literature is typically illustrated only by simple examples. Moreover, the integration of model-based decision support methodologies and tools with specialized model-based knowledge developed for handling real problems in environmental, engineering, industrial, economical, social and political activities is often not satisfactory. Therefore, there is a need to present the state of art of methodology and tools for development of model-based decision support systems, and illustrate this state by applications to various complex real-world decision problems. The monograph reports many years of experience of many researchers, who have not only contributed to the developments in operations research but also succeeded to integrate knowledge and craft of various disciplines into several modern decision support systems which have been applied to actual complex decision-making processes in various fields of policy making. The experience presented in this book will be of value to researchers and practitioners in various fields. The issues discussed in this book gain in importance with the development of the new era of the information society, where information, knowledge, and ways of processing them become a decisive part of human activities. The examples presented in this book illustrate how how various methods and tools of model-based decision support can actually be used for helping modern decision makers that face complex problems. Overview of the contents: The first part of this three-part book presents the methodological background and characteristics of modern decision-making environment, and the value of model-based decision support thus addressing current challenges of decision support. It also provides the methodology of building and analyzing mathematical models that represent underlying physical and economic processes, and that are useful for modern decision makers at various stages of decision making. These methods support not only the analysis of Pareto-efficient solutions that correspond best to decision maker preferences but also allow the use of other modeling concepts like soft constraints, soft simulation, or inverse simulation. The second part describes various types of tools that are used for the development of decision support systems. These include tools for modeling, simulation, optimization, tools supporting choice and user interfaces. The described tools are both standard, commercially available, and nonstandard, public domain or shareware software, which are robust enough to be used also for complex applications. All four environmental applications (regional water quality management, land use planning, cost-effective policies aimed at improving the European air quality, energy planning with environmental implications) presented in the third part of the book rely on many years of cooperation between the authors of the book with several IIASA's projects, and with many researchers from the wide IIASA network of collaborating institutions. All these applications are characterized by an intensive use of model-based decision support. Finally, the appendix contains a short description of some of the tools described in the book that are available from IIASA, free of charge, for research and educational purposes. The experiences reported in this book indicate that the development of DSSs for strategic environmental decision making should be a joint effort involving experts in the subject area, modelers, and decision support experts. For the other experiences discussed in this book, the authors stress the importance of good data bases, and good libraries of tools. One of the most important requirements is a modular structure of a DSS that enhances the reusability of system modules. In such modular structures, user interfaces play an important role. The book shows how modern achievements in mathematical programming and computer sciences may be exploited for supporting decision making, especially about strategic environmental problems. It presents the methodological background of various methods for model-based decision support and reviews methods and tools for model development and analysis. The methods and tools are amply illustrated with extensive applications. Audience: This book will be of interest to researchers and practitioners in the fields of model development and analysis, model-based decision analysis and support, (particularly in the environment, economics, agriculture, engineering, and negotiations areas) and mathematical programming. For understanding of some parts of the text a background in mathematics and operational research is required but several chapters of the book will be of value also for readers without such a background. The monograph is also suitable for use as a text book for courses on advanced (Master and Ph.D.) levels for programs on Operations Research, decision analysis, decision support and various environmental studies (depending on the program different parts of the book may be emphasized).

A cooperative system is a collection of dynamical objects, which communicate and cooperate in order to achieve a common or shared objective. The cooperation of entities is achieved through communication; either explicitly by message passing, or implicitly via observation of another entities' state. As in natural systems, cooperation may assume a hierarchical form and the control processes may be distributed or decentralized. Due to the dynamic nature of individuals and the interaction between them, the problems associated with cooperative systems typically involve many uncertainties. Moreover, in many cases cooperative systems are required to operate in a noisy or hazardous environment, which creates special challenges for designing the control process.

During the last decades, considerable progress has been observed in all aspects regarding the study of cooperative systems including modeling of cooperative systems, resource allocation, discrete event driven dynamical control, continuous and hybrid dynamical control, and theory of the interaction of information, control, and hierarchy. Solution methods have been proposed using control and optimization approaches, emergent rule based techniques, game theoretic and team theoretic approaches. Measures of performance have been suggested that include the effects of hierarchies and information structures on solutions, performance bounds, concepts of convergence and stability, and problem complexity. These and other topics were discusses at the Second Annual Conference on Cooperative Control and Optimization in Gainesville, Florida. Refereed papers written by selected conference participants from the conference are gathered in this volume, which presents problem models, theoretical results, and algorithms for various aspects of cooperative control.

Audience: The book is addressed to faculty, graduate students, and researchers in optimization and control, computer sciences and engineering.

The Summer School has been dedicated to one of the proponents and ?rst Chairman of the Strategy Board of MACSI-net, the late Jacques Louis Lions (see the dedication by Roland Glowinski). MACSI-net is a European Network of Excellence, where both enterprises and university institutions co-operate to solve challenging problems to their mutual bene?t. In particular the network focuses on strategies to enhance interactions between industry and academia. The aim is to help industry (in particular SMEs) alert academia about industrial needs in terms of advanced mathematical and computational methods and tools. The network is mul- disciplinary oriented, combining the power of applied mathematics, scienti?c computing and engineering, for modeling and simulation. It was set up by a joint e?ort of ECCOMAS and ECMI European associations. Thisparticularevent,occurredduringMarch17-22,2003,wasajointe?ort ofthe TrainingCommittee (chairedby VC)andIndustrialRelationsComm- tee (chairedby JP)to alert both Academia and Industry about the increasing role of Multidisciplinary Methods and Tools for the design of complex pr- uctsinvariousareasofindustrialinterest.Thisincreasingcomplexityisdriven by societal constraints to be satis? ed in a simultaneous and a?ordable way. The mastering of complexity implies the sharing of di?erent tools by di?erent actors which require much higher level of communication between culturally di?erent people. The school o?ered to young researchers the opportunity to be exposed to the presentation of real industrial and societal problems and the relevant innovative methods used; the need of further contributions from mathematics to improve or provide better solutions had also been considered.

The vast majority of important applications in science, engineering and applied science are characterized by the existence of multiple minima and maxima, as well as first, second and higher order saddle points. The area of Deterministic Global Optimization introduces theoretical, algorithmic and computational ad vances that (i) address the computation and characterization of global minima and maxima, (ii) determine valid lower and upper bounds on the global minima and maxima, and (iii) address the enclosure of all solutions of nonlinear con strained systems of equations. Global optimization applications are widespread in all disciplines and they range from atomistic or molecular level to process and product level representations. The primary goal of this book is three fold: first, to introduce the reader to the basics of deterministic global optimization; second, to present important theoretical and algorithmic advances for several classes of mathematical prob lems that include biconvex and bilinear; problems, signomial problems, general twice differentiable nonlinear problems, mixed integer nonlinear problems, and the enclosure of all solutions of nonlinear constrained systems of equations; and third, to tie the theory and methods together with a variety of important applications."

At present, in order to resolve problems of ecology and to save mineral resources for future population generations, it is quite necessary to know how to maintain nature arrangement in an efficient way. It is possible to achieve a rational nature arrangement when analyzing solutions to problems concerned with optimal control of distributed systems and with optimization of modes in which main ground medium processes are functioning (motion of liquids, generation of temperature fields, mechanical deformation of multicomponent media). Such analysis becomes even more difficult because of heterogeneity of the region that is closest to the Earth surface, and thin inclusions/cracks in it exert their essential influence onto a state and development of the mentioned processes, especially in the cases of mining. Many researchers, for instance, A.N. Tikhonov - A.A. Samarsky [121], L. Luckner - W.M. Shestakow [65], Tien-Mo Shih, K.L. Johnson [47], E. Sanchez-Palencia [94] and others stress that it is necessary to consider how thin inclusions/cracks exert their influences onto development of these processes, while such inclusions differ in characteristics from main media to a considerable extent (moisture permeability, permeability to heat, bulk density or shear strength may be mentioned). Xll An influence exerted from thin interlayers onto examined processes is taken into account sufficiently adequately by means of various constraints, namely, by the conjugation conditions [4, 8, 10, 15, 17-20, 22-26, 38, 44, 47, 52, 53, 68, 76, 77, 81, 83, 84, 90, 95, 96-100, 112-114, 117, 123].

Targeted audience * Specialists in numerical computations, especially in numerical optimiza tion, who are interested in designing algorithms with automatie result ver ification, and who would therefore be interested in knowing how general their algorithms caIi in principle be. * Mathematicians and computer scientists who are interested in the theory 0/ computing and computational complexity, especially computational com plexity of numerical computations. * Students in applied mathematics and computer science who are interested in computational complexity of different numerical methods and in learning general techniques for estimating this computational complexity. The book is written with all explanations and definitions added, so that it can be used as a graduate level textbook. What this book .is about Data processing. In many real-life situations, we are interested in the value of a physical quantity y that is diflicult (or even impossible) to measure directly. For example, it is impossible to directly measure the amount of oil in an oil field or a distance to a star. Since we cannot measure such quantities directly, we measure them indirectly, by measuring some other quantities Xi and using the known relation between y and Xi'S to reconstruct y. The algorithm that transforms the results Xi of measuring Xi into an estimate fj for y is called data processing.

Optimization in Computational Chemistry and Molecular Biology: Local and Global Approaches covers recent developments in optimization techniques for addressing several computational chemistry and biology problems. A tantalizing problem that cuts across the fields of computational chemistry, biology, medicine, engineering and applied mathematics is how proteins fold. Global and local optimization provide a systematic framework of conformational searches for the prediction of three-dimensional protein structures that represent the global minimum free energy, as well as low-energy biomolecular conformations. Each contribution in the book is essentially expository in nature, but of scholarly treatment. The topics covered include advances in local and global optimization approaches for molecular dynamics and modeling, distance geometry, protein folding, molecular structure refinement, protein and drug design, and molecular and peptide docking. Audience: The book is addressed not only to researchers in mathematical programming, but to all scientists in various disciplines who use optimization methods in solving problems in computational chemistry and biology.