Springer Optimization and Its Applications

Latest release: January 4, 2024
Series
198
Books
Optimization in Public Transportation: Stop Location, Delay Management and Tariff Zone Design in a Public Transportation Network
Book 3·Jan 2007
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Customer-Oriented Optimization in Public Transportation develops models, results and algorithms for optimizing public transportation from a customer-oriented point of view. 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. An appendix summarizes some of the basics of optimization needed to interpret the material in the book.

In detail, the topics the book covers in its three parts are as follows:

1. Stop location. Does it make sense to open new stations along existing bus or railway lines? If yes, in which locations? The problem is modeled as a continuous covering problem. To solve it the author develops a finite dominating set and shows that efficient methods are possible if the special structure of the covering matrix is used.

2. Delay management. Should a train wait for delayed feeder trains or should it depart in time? The author builds up two different integer programming models and a model based on project planning methods. Properties and solution methods are developed.

3. Tariff planning. Part 3 deals with the design of zone tariff systems, in which the fare is determined by the number of zones used by the passengers. The author presents a model for this problem and approaches based on clustering theory.

Models and Algorithms for Global Optimization: Essays Dedicated to Antanas Žilinskas on the Occasion of His 60th Birthday
Book 4·Apr 2007
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Antanas ~ilinskas was born on January 5, 1946 in Lithuania. He graduated with a gold medal from 2nd Kaunas Gymnasium in 1963 and with a distinction diploma of Electrical Engineering from Kaunas University of Technology in 1968. His Ph. D. studies (aspirantur) at Lithuanian Academy of Sciences lasted from 1970 to 1973. The Candidate of Sciences (Ph. D. ) degree in Technical - bernetics (1973) has been received from Kaunas University of Technology. The Doctor of Mathematical Sciences degree (Habilitation, 1985) has been received from St. Petersburg (Leningrad) University. The title Senior Research Fellow (1980) has been conferred by the Presidium of Academy of Sciences, and the title Professor (1989) by Vilnius Pedagogical University. He has been awarded (with V. saltenis and G. Dzemyda) Lithuanian National Award for scientific achievements of 2001 for the research on "Efficient optimization methods and their applications". A. ~ilinskas joined the Institute of Mathematics and Informatics in 1973 starting with a position of junior research associate, worked as a senior - search associate reaching the highest rank of principal researcher which is his main position now. Apart from working in the research institute he was a lecturer at Vilnius Pedagogical University 1986-1988, where he founded a - partment of Informatics in 1988 and held a position of professor and head of this department 1988-1993. He worked later as a professor of this department until 2000.
Differential Evolution: In Search of Solutions
Book 5·Feb 2007
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Di?erential evolution is one of the most recent global optimizers. Discovered in 1995 it rapidly proved its practical e?ciency. This book gives you a chance to learn all about di?erential evolution. On reading it you will be able to pro?tably apply this reliable method to problems in your ?eld. Asforme,mypassionforintelligentsystemsandoptimizationbeganasfar back as during my studies at Moscow State Technical University of Bauman, the best engineering school in Russia. At that time, I was gathering material for my future thesis. Being interested in my work, the Mining School of Paris proposed that I write a dissertation in France. I hesitated some time over a choice, but my natural curiosity and taste for novelty ?nally prevailed. At ́ present, Docteur ` es science en informatique de l’EcoledesMinesdeParis,I am concentrating on the development of my own enterprise. If optimization is my vocation, my hobbies are mathematics and music. Although mathematics disciplines the mind, music is ?lled with emotions. While playing my favorite composition, I decided to write this book. The purpose of the book is to give, in a condensed but overview form, a description of di?erential evolution. In addition, this book makes accessible to a wide audience the fruits of my long research in optimization. Namely, I laid the foundation of the universal concept of search strategies design, suitable not only for di?erential evolution but for many other algorithms. Also, I introduced a principle of energetic selection, an e?cient method of hybridization, and advanced paralleling techniques.
Set-Valued Mappings and Enlargements of Monotone Operators
Book 8·Nov 2007
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Set-valued analysis is an essential tool for the mathematical formulation of many real-life situations, e.g., equilibrium theory in mathematical economics. This work offers the first comprehensive treatment in book form of the fairly new subdiscipline of enlargements of maximal monotone operators, including several important new results in the field. In the last decades, with the development of nonsmooth optimization, effective algorithms have been developed to solve these kinds of problems, such as nonsmooth variational inequalities. Several of these methods, such as bundle methods for variational problems, are fully developed and analyzed in this book.

The first chapters provide a self-contained review of the basic notions and fundamental results in set-valued analysis, including set convergence and continuity of set-valued mappings together with many important results in infinite-dimensional convex analysis, leading to the classical fixed point results due to Ekeland, Caristi and Kakutani. Next, an in-depth introduction to monotone operators is developed, emphasizing results related to maximality of subdifferentials and of sums of monotone operators. Building on this foundational material, the second part of the monograph contains new results (all of them established during the last decade) on the concept of enlargements of monotone operators, with applications to variational inequalities, bundle-type methods, augmented Lagrangian methods, and proximal point algorithms.

Audience:
This book is addressed to mathematicians, engineers, economists, and researchers interested in acquiring a solid mathematical foundation in topics such as point-to-set operators, variational inequalities, general equilibrium theory, and nonsmooth optimization, among others. Containing extensive exercises and examples throughout the text, the first four chapters of the book can also be used for a one-quarter course in set-valued analysis and maximal monotone operators for graduate students in pure and applied mathematics, mathematical economics, operations research and related areas. The only requisites, besides a minimum level of mathematical maturity, are some basic results of general topology and functional analysis.

Stochastic Global Optimization
Book 9·Nov 2007
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This book aims to cover major methodological and theoretical developments in the ?eld of stochastic global optimization. This ?eld includes global random search and methods based on probabilistic assumptions about the objective function. We discuss the basic ideas lying behind the main algorithmic schemes, formulate the most essential algorithms and outline the ways of their theor- ical investigation. We try to be mathematically precise and sound but at the same time we do not often delve deep into the mathematical detail, referring instead to the corresponding literature. We often do not consider the most g- eral assumptions, preferring instead simplicity of arguments. For example, we only consider continuous ?nite dimensional optimization despite the fact that some of the methods can easily be modi?ed for discrete or in?nite-dimensional optimization problems. The authors’ interests and the availability of good surveys on particular topics have in uenced the choice of material in the book. For example, there are excellent surveys on simulated annealing (both on theoretical and - plementation aspects of this method) and evolutionary algorithms (including genetic algorithms). We thus devote much less attention to these topics than they merit, concentrating instead on the issues which are not that well d- umented in literature. We also spend more time discussing the most recent ideas which have been proposed in the last few years.
Nonsmooth Vector Functions and Continuous Optimization
Book 10·Oct 2007
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A recent significant innovation in mathematical sciences has been the progressive use of nonsmooth calculus, an extension of the differential calculus, as a key tool of modern analysis in many areas of mathematics, operations research, and engineering. Focusing on the study of nonsmooth vector functions, this book presents a comprehensive account of the calculus of generalized Jacobian matrices and their applications to continuous nonsmooth optimization problems and variational inequalities in finite dimensions.

The treatment is motivated by a desire to expose an elementary approach to nonsmooth calculus by using a set of matrices to replace the nonexistent Jacobian matrix of a continuous vector function. Such a set of matrices forms a new generalized Jacobian, called pseudo-Jacobian. A direct extension of the classical derivative that follows simple rules of calculus, the pseudo-Jacobian provides an axiomatic approach to nonsmooth calculus, a flexible tool for handling nonsmooth continuous optimization problems.

Illustrated by numerous examples of known generalized derivatives, the work may serve as a valuable reference for graduate students, researchers, and applied mathematicians who wish to use nonsmooth techniques and continuous optimization to model and solve problems in mathematical programming, operations research, and engineering. Readers require only a modest background in undergraduate mathematical analysis to follow the material with minimal effort.

Optimization and Control of Bilinear Systems: Theory, Algorithms, and Applications
Book 11·Mar 2010
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The present book is based on results of scienti?c investigations and on the materials of special courses, o?ered for graduate and undergraduate students. The purpose of this book is to acquaint the reader with the developments in bilinear systems theory and its applications. Particular attention is paid to control of open physical processes functioning in a nonequilibrium mode. The text consists of eight chapters. Chapter 1 is concerned with the problems of systems analysis of bilinear processes. Chapter 2 solves the problem of optimal control of bilinear systems on the basis of di?er- tial geometry methods. Chapter 3 deals with the progress made in an adaptive estimation technique. Chapter 4 is devoted to the application of the Yang–Mills ?elds to investigation of nonlinear control problems. Chapter 5 considers intelligent sensors, used to examine weak signals. This chapter also describes and analyzes bilinear models of intelligent sensing elements. Chapter 6 illustrates control problems of a quantum system. Chapter 7 discusses the problems of control and identi?cation in systems with chaotic dynamics. Finally, Chapter 8 examines the c- trolled processes running in biomolecular systems. This book is directed to students, postgraduate students, and speci- ists engaged in the ?elds of control of physical processes, quantum and molecular computing, biophysics, and physical information science.
Optimization in Medicine
Book 12·Dec 2007
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Optimization has become an essential tool in addressing the limitation of resources and need for better decision-making in the medical field. Both continuous and discrete mathematical techniques are playing an increasingly important role in understanding several fundamental problems in medicine.

This volume presents a wide range of medical applications that can utilize mathematical computing. Examples include using an algorithm for considering the seed reconstruction problem in brachytherapy and using optimization-classification models to assist in the early prediction, diagnosis and detection of diseases. Discrete optimization techniques and measures derived from the theory of nonlinear dynamics, with analysis of multi-electrode electroencephalographic (EEG) data, assist in predicting impending epileptic seizures. Mathematics in medicine can also be found in recent cancer research. Sophisticated mathematical models and optimization algorithms have been used to generate treatment plans for radionuclide implant and external beam radiation therapy. Optimization techniques have also been used to automate the planning process in Gamma Knife treatment, as well as to address a variety of medical image registration problems.

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.

Nonlinear Optimization with Engineering Applications
Book 19·Dec 2008
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This book, like its companion volume Nonlinear Optimization with Financial Applications, is an outgrowth of undergraduate and po- graduate courses given at the University of Hertfordshire and the University of Bergamo. It deals with the theory behind numerical methods for nonlinear optimization and their application to a range of problems in science and engineering. The book is intended for ?nal year undergraduate students in mathematics (or other subjects with a high mathematical or computational content) and exercises are provided at the end of most sections. The material should also be useful for postg- duate students and other researchers and practitioners who may be c- cerned with the development or use of optimization algorithms. It is assumed that readers have an understanding of the algebra of matrices and vectors and of the Taylor and mean value theorems in several va- ables. Prior experience of using computational techniques for solving systems of linear equations is also desirable, as is familiarity with the behaviour of iterative algorithms such as Newton’s methodfor nonlinear equations in one variable. Most of the currently popular methods for continuous nonlinear optimization are described and given (at least) an intuitive justi?cation. Relevant convergence results are also outlined and we provide proofs of these when it seems instructive to do so. This theoretical material is complemented by numerical illustrations which give a ?avour of how the methods perform in practice.
Decision Modeling and Behavior in Complex and Uncertain Environments
Book 21·Jul 2008
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On February 27 and 28 of 2006, the University of Arizona held a workshop entitled, “Decision Modeling and Behavior in Uncertain and Complex En- ronments,” sponsored by the Air Force O?ce of Scienti?c Research under a Multidisciplinary University Research Initiative (MURI) grant. The purpose of the workshop was to assemble preeminent researchers studying problems at the interface of behavioral and cognitive science, decision analysis, and operations research. This book is a compilation of 14 chapters based on the presentations given during the workshop. These contributions are grouped into four general areas, which describe in some detail the challenges in conducting novel research in this ?eld. Part One is concerned with the need for integrating decision analysis and behavioral models. Robert T. Clemen discusses how the ?elds of behavioral - search and decision analysis have diverged over time, and makes a compelling case to establish new links between the disciplines. He recommends leveraging lessons learned from behavioral studies within prescriptive decision analysis studies and evaluating the practical impact of those prescriptive techniques in helping decision makers achieve their objectives. Jenna L. Marquard and Stephen M. Robinson address eleven common “traps” that face decision model analysts and users. An understanding of these traps leads to an understanding of modeling features that either help or hurt the decision-making process. The authors link theory and practice by examining a set of case studies across a diverse array of model scenarios, and provide a checklist of recommendations for analysts confronted by these eleven traps.