Panos M. Pardalos - Böcker

Optimization is an essential tool in every project in every large-scale organization, whether in business, industry, engineering, or science. In recent years, algorithmic advances and software and hardware improvements have given managers a powerful framework for making key decisions about everything from production planning to scheduling distribution.This comprehensive resource brings together in one volume the major advances in the field. Distinguished contributors focus on the algorithmic and computational aspects of optimization, particularly the most recent methods for solving a wide range of decision-making problems. The book is divided into three main sections: algorithms, covering every type of programming; applications, where computational tools are put to work solving tasks in planning, production, distribution, scheduling and other decisions in project management; and software, a comprehensive introduction to languages and systems. Designed as a practical resource for programmers, project planners, and managers, it covers optimization problems in a wide range of settings, from the airline and aerospace industries to telecommunications, finance, health systems, biomedicine, and engineering.

Handbook of Optimization in Medicine is devoted to examining the dramatic increase in the application of effective optimization techniques to the delivery of health care. The articles, written by experts from the areas of operations research, computer science, and medicine, focus on models and algorithms that have led to more efficient and sophisticated treatments of patients.Topics covered include: optimization in medical imaging, classification and data mining with medical applications, treatment of epilepsy and other brain disorders, treatment of head-and-neck, prostate, and other cancers using conventional conformal and intensity-modulated radiation therapy as well as proton therapy, treatment selection for breast cancer based on new classification schemes, optimization for the genome project, optimal timing of organ transplants.

In February 2002, the Industrial and Systems Engineering (ISE) De partment at the University of Florida hosted a National Science Founda tion Workshop on Collaboration and Negotiation in Supply Chain Man agement and E Commerce. This workshop focused on characterizing the challenges facing leading edge firms in supply chain management and electronic commerce, and identifying research opportunities for de veloping new technological and decision support capabilities sought by industry. The audience included practitioners in the areas of supply chain management and E Commerce, as well as academic researchers working in these areas. The workshop provided a unique setting that has facilitated ongoing dialog between academic researchers and industry practitioners. This book codifies many of the important themes and issues around which the workshop discussions centered. The editors of this book, all faculty members in the ISE Department at the University of Florida, also served as the workshop's coordinators. In addition to workshop participants, we also invited contributions from leading academics and practitioners who were not able to attend. As a result, the chapters herein represent a collection of research contributions, monographs, and case studies from a variety of disciplines and viewpoints. On the aca demic side alone, chapter authors include faculty members in supply chain and operations management, marketing, industrial engineering, economics, computer science, civil and environmental engineering, and building construction departments.

Supply Chain Optimization captures the latest results in a segment of current research activity in supply chain management. This research area focuses on applying optimization techniques to supply chain management problems. The research papers that make up the volume provide a snapshot of state-of-the-art optimization methods within the field. This book presents rigorous modelling approaches for supply chain operations problems with a goal of improving supply chain performance (or the performance of some segment thereof). It contains high-quality works from leading researchers in the field whose expertise fits within this scope. The book provides a diverse blend of research topics and novel modelling and solution approaches for difficult classes of supply chain operations, planning, and design problems.

Robust design—that is, managing design uncertainties such as model uncertainty or parametric uncertainty—is the often unpleasant issue crucial in much multidisciplinary optimal design work. Recently, there has been enormous practical interest in strategies for applying optimization tools to the development of robust solutions and designs in several areas, including aerodynamics, the integration of sensing (e.g., laser radars, vision-based systems, and millimeter-wave radars) and control, cooperative control with poorly modeled uncertainty, cascading failures in military and civilian applications, multi-mode seekers/sensor fusion, and data association problems and tracking systems. The contributions to this book explore these different strategies. The expression "optimization-directed” in this book’s title is meant to suggest that the focus is not agonizing over whether optimization strategies identify a true global optimum, but rather whether these strategies make significant design improvements.

As optimization researchers tackle larger and larger problems, scale interactions play an increasingly important role. One general strategy for dealing with a large or difficult problem is to partition it into smaller ones, which are hopefully much easier to solve, and then work backwards towards the solution of original problem, using a solution from a previous level as a starting guess at the next level. This volume contains 22 chapters highlighting some recent research. The topics of the chapters selected for this volume are focused on the development of new solution methodologies, including general multilevel solution techniques, for tackling difficult, large-scale optimization problems that arise in science and industry. Applications presented in the book include but are not limited to the circuit placement problem in VLSI design, a wireless sensor location problem, optimal dosages in the treatment of cancer by radiation therapy, and facility location.

Telecommunications has had a major impact in all aspects of life in the last century. There is little doubt that the transformation from the industrial age to the information age has been fundamentally influenced by advances in telecommunications. Optimization problems are abundant in the telecommunications industry. The successful solution of these problems has played an important role in the development of telecommunications and its widespread use. Optimization problems arise in the design of telecommunication systems and in their operation. The Handbook of Optimization in Telecommunications brings together experts from around the world who use optimization to solve problems that arise in telecommunications. The editors made an effort to cover recent optimization developments that are frequently applied to telecommunications. The spectrum of topics covered includes planning and design of telecommunication networks, routing, network protection, grooming, restoration, wireless communications, network location and assignment problems, Internet protocol, World Wide Web, and stochastic issues in telecommunications. The editors’ objective is to provide a reference tool for the increasing number of scientists and engineers in telecommunications who depend upon optimization in some way.Each chapter in the handbook is of an expository nature, but of scholarly treatment, and includes a brief overview of the state-of-the-art thinking relative to the topic, as well as pointers to the key references in the field. Specialists as well as nonspecialists should find this handbook stimulating and helpful.

This volume presents an extensive collection of contributions covering aspects of the exciting and important research field of data mining techniques in biomedicine. Coverage includes new approaches for the analysis of biomedical data; applications of data mining techniques to real-life problems in medical practice; comprehensive reviews of recent trends in the field. The book addresses incorporation of data mining in fundamental areas of biomedical research: genomics, proteomics, protein characterization, and neuroscience.

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.

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.

The goal of the Encyclopedia of Optimization is to introduce the reader to a complete set of topics that show the spectrum of research, the richness of ideas, and the breadth of applications that has come from this field.In 2000, the first edition was widely acclaimed and received high praise. J.B. Rosen crowned it “an indispensable resource” and Dingzhu Du lauded it as “the standard most important reference in this very dynamic research field”. Top authors such as Herbert Hauptman (winner of the Nobel Prize) and Leonid Khachiyan (the Ellipsoid theorist) contributed and the second edition keeps these seminal entries.The second edition builds on the success of the former edition with more than 150 completely new entries, designed to ensure that the reference addresses recent areas where optimization theories and techniques have advanced. Particularly heavy attention resulted in health science and transportation, with entries such as “Algorithms for Genomics”, “Optimization and Radiotherapy Treatment Design”, and “Crew Scheduling”.

Agriculture has experienced a dramatic change during the past decades. The change has been structural and technological. Structural changes can be seen in the size of current farms; not long ago, agricultural production was organized around small farms, whereas nowadays the agricultural landscape is dominated by large farms. Large farms have better means of applying new technologies, and therefore technological advances have been a driving force in changing the farming structure. New technologies continue to emerge, and their mastery and use in requires that farmers gather more information and make more complex technological choices. In particular, the advent of the Internet has opened vast opportunities for communication and business opportunities within the agricultural com- nity. But at the same time, it has created another class of complex issues that need to be addressed sooner rather than later. Farmers and agricultural researchers are faced with an overwhelming amount of information they need to analyze and synthesize to successfully manage all the facets of agricultural production. This daunting challenge requires new and complex approaches to farm management. A new type of agricultural management system requires active cooperation among multidisciplinary and multi-institutional teams and ref- ing of existing and creation of new analytical theories with potential use in agriculture. Therefore, new management agricultural systems must combine the newest achievements in many scientific domains such as agronomy, economics, mathematics, and computer science, to name a few.

This comprehensive edited volume discusses the most recent advances within the field of financial engineering, focusing not only on the description of the existing areas in financial engineering research, but also on the new methodologies that have been developed for modeling and addressing financial engineering problems.

This comprehensive work examines important recent developments and modern applications in the fields of optimization, control, game theory and equilibrium programming. In particular, the concepts of equilibrium and optimality are of immense practical importance affecting decision-making problems regarding policy and strategies, and in understanding and predicting systems in different application domains, ranging from economics and engineering to military applications. The book consists of 29 survey chapters written by distinguished researchers in the above areas.

Data Mining in Agriculture represents a comprehensive effort to provide graduate students and researchers with an analytical text on data mining techniques applied to agriculture and environmental related fields. This book presents both theoretical and practical insights with a focus on presenting the context of each data mining technique rather intuitively with ample concrete examples represented graphically and with algorithms written in Matlab®. Examples and exercises with solutions are provided at the end of each chapter to facilitate the comprehension of the material. For each data mining technique described in the book variants and improvements of the basic algorithm are also given.

In a world with highly competitive markets and economic instability due to capitalization, industrial competition has increasingly intensified. In order for many industries to survive and succeed, they need to develop highly effective coordination between supply chain partners, dynamic collaborative and strategic alliance relationships, and efficient logistics and supply chain network designs. Consequently, in the past decade, there has been an explosion of interest among academic researchers and industrial practitioners in innovative supply chain and logistics models, algorithms, and coordination policies. Mathematically distinct from classical supply chain management, this emerging research area has been proven to be useful and applicable to a wide variety of industries. This book brings together recent advances in supply chain and logistics research and computational optimization that apply to a collaborative environment in the enterprise.

In recent years, technological advances have resulted in the rapid development of a new exciting research direction --- the interdisciplinary use of sensors for data collection, systems analysis, and monitoring.  Application areas include environmental monitoring, military surveillance, computational neuroscience, seismic detection, and many more. Among the research areas considered, sensor networks represent a very active area, as well as work on problems such as sensor networks, sensor network localization, and network design. They are also related to optimization problems that have multiple applications and require interdisciplinary techniques from several fields. Additionally, neuroscientists use sensors to collect data during tests which record brain activity.  These highly calibrated sensors require precision engineering techniques play an important role in analyzing and integrating large datasets.The purpose of this book is to bring together recent developments of both theoreticians and practitioners representing various fields from engineering, computer science, biomedicine, and the military, share knowledge, ideas, and techniques regarding the state-of-the-art sensor research.

This book represents a collection of recent advances in computational studies in neuroscience research that practically applies to a collaborative and integrative environment in engineering and medical domains. This work has been designed to address the explosion of interest by academic researchers and practitioners in highly-effective coordination between computational models and tools and quantitative investigation of neuroscientific data. To bridge the vital gap between science and medicine, this book brings together diverse research areas ranging from medical signal processing, image analysis, and data mining to neural network modeling, regulation of gene expression, and brain dynamics. We hope that this work will also be of value to investigators and practitioners in academic institutions who become involved in computational modeling as an aid in translating information in neuroscientific data to their colleagues in medical - main. This volume will be very appealing to graduate (and advanced undergraduate) students, researchers, and practitioners across a wide range of industries (e. g. , pharmaceutical, chemical, biological sciences), who require a detailed overview of the practical aspects of computational modeling in real-life neuroscience problems. For this reason, our audience is assumed to be very diverse and heterogenous, including: vii viii Preface • researchers from engineering, computer science, statistics, and mathematics - mains as well as medical and biological scientists; •physicians working in scienti?c research to understand how basic science can be linked with biological systems.

During the last four decades there has been a remarkable development in optimization and optimal control. Due to its wide variety of applications, many scientists and researchers have paid attention to fields of optimization and optimal control. A huge number of new theoretical, algorithmic, and computational results have been observed in the last few years. This book gives the latest advances, and due to the rapid development of these fields, there are no other recent publications on the same topics.Key features:Provides a collection of selected contributions giving a state-of-the-art account of recent developments in the fieldCovers a broad range of topics in optimization and optimal control, including unique applicationsIncludes chapters written by experts in their respective disciplinesAppeals to a broad audience of researchers, practitioners, and advanced graduate students in applied mathematics and engineering

In the past two decades, breakthroughs in computer technology have made a tremendous impact on optimization. In particular, availability of parallel computers has created substantial interest in exploring the use of parallel processing for solving discrete and global optimization problems. The chapters in this volume cover a broad spectrum of recent research in parallel processing of discrete and related problems. The topics discussed include distributed branch-and-bound algorithms, parallel genetic algorithms for large scale discrete problems, simulated annealing, parallel branch-and-bound search under limited-memory constraints, parallelization of greedy randomized adaptive search procedures, parallel optical models of computing, randomized parallel algorithms, general techniques for the design of parallel discrete algorithms, parallel algorithms for the solution of quadratic assignment and satisfiability problems. The book will be a valuable source of information to faculty, students and researchers in combinatorial optimization and related areas.

This book will present the papers delivered at the first U.S. conference devoted exclusively to global optimization and will thus provide valuable insights into the significant research on the topic that has been emerging during recent years. Held at Princeton University in May 1991, the conference brought together an interdisciplinary group of the most active developers of algorithms for global optimization in order to focus the attention of the mathematical programming community on the unsolved problems and diverse applications of this field. The main subjects addressed at the conference were advances in deterministic and stochastic methods for global optimization, parallel algorithms for global optimization problems, and applications of global optimization. Although global optimization is primarily a mathematical problem, it is relevant to several other disciplines, including computer science, applied mathematics, physical chemistry, molecular biology, statistics, physics, engineering, operations research, communication theory, and economics. Global optimization problems originate from a wide variety of mathematical models of real-world systems.Some of its applications are allocation and location problems and VLSI and data-base design problems. Originally published in 1991. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.

This book will present the papers delivered at the first U.S. conference devoted exclusively to global optimization and will thus provide valuable insights into the significant research on the topic that has been emerging during recent years. Held at Princeton University in May 1991, the conference brought together an interdisciplinary group of the most active developers of algorithms for global optimization in order to focus the attention of the mathematical programming community on the unsolved problems and diverse applications of this field. The main subjects addressed at the conference were advances in deterministic and stochastic methods for global optimization, parallel algorithms for global optimization problems, and applications of global optimization. Although global optimization is primarily a mathematical problem, it is relevant to several other disciplines, including computer science, applied mathematics, physical chemistry, molecular biology, statistics, physics, engineering, operations research, communication theory, and economics. Global optimization problems originate from a wide variety of mathematical models of real-world systems.Some of its applications are allocation and location problems and VLSI and data-base design problems. Originally published in 1991. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.

This book is a collection of papers presented at the Large Scale Optimization Conference held at the Center for Applied Optimization, University of Florida, Gainesville, in February, 1993. Accurate modelling of scientific problems often leads to the formulation of large-scale optimization problems involving thousands of continuous and/or discrete variables. As a consequence of new algorithmic developments and of the increased power of computers, large-scale optimization has seen a dramatic increase in activities in the past decade. Topics include large-scale linear, nonlinear and stochastic programming, network optimization, decomposition methods, methods for optimal control, non-smooth equations, integer programming and software development. In addition, applications are included in location theory, structural mechanics, molecular configuration, transportation, multi-target tracking and database design. The book aims to provide a useful source of information for faculty, students and researchers in mathematical programming and related fields.

Global optimization is concerned with the computation and characterization of global optima of nonlinear functions. During the past three decades the field of global optimization has been growing at a rapid pace, and the number of publications on all aspects of global optimization has been increasing steadily. Many applications, as well as new theoretical, algorithmic, and computational contributions have resulted. Each contribution in this text is essentially expository in nature, but scholarly in its treatment. The chapters cover: optimality conditions; complexity results; concave minimization; DC programming; general quadratic programming; nonlinear complementarity; minimax problems; multiplicative programming; Lipschitz optimization; fractional programming; network problems; trajectory methods; homotopy methods, interval methods; and stochastic approaches. This book is addressed to researchers in mathematical programming, as well as all scientists who use optimization methods to model and solve problems.

Global optimization concerns the computation and characterization of global optima of nonlinear functions. Such problems are widespread in the mathematical modelling of real systems in a very wide range of applications, and recent years have seen the development of many new theoretical, algorithmic and computational contributions which have helped to solve globally multi-extreme problems in important practical applications. Most of the existing books on optimization focus on the problem of computing locally optimal solutions. This is a textbook on constrained global optimization that covers the fundamentals of the subject, presenting material including algorithms, applications and complexity results for quadratic programming, concave minimization, DC and Lipschitz problems, and nonlinear network flow. Each chapter contains examples and ends with selected exercises, designed to help students grasp the material and enhance their knowledge of the methods involved.It is designed for students of mathematical programming, and all scientists, from whatever discipline, who need global optimization methods in such diverse areas as economic modelling, fixed charges, finance, networks and transportation, databases, chip design, image processing, nuclear and mechanical design, chemical engineering design and control, molecular biology, and environmental engineering.

Global optimization concerns the computation and characterization of global optima of nonlinear functions. Such problems are widespread in the mathematical modelling of real systems in a very wide range of applications, and recent years have seen the development of many new theoretical, algorithmic and computational contributions which have helped to solve globally multi-extreme problems in important practical applications. Most of the existing books on optimization focus on the problem of computing locally optimal solutions. This is a textbook on constrained global optimization that covers the fundamentals of the subject, presenting material including algorithms, applications and complexity results for quadratic programming, concave minimization, DC and Lipschitz problems, and nonlinear network flow. Each chapter contains examples and ends with selected exercises, designed to help students grasp the material and enhance their knowledge of the methods involved.It is designed for students of mathematical programming, and all scientists, from whatever discipline, who need global optimization methods in such diverse areas as economic modelling, fixed charges, finance, networks and transportation, databases, chip design, image processing, nuclear and mechanical design, chemical engineering design and control, molecular biology, and environmental engineering.

Classical minimax theory (von Neumann), duality and saddle point analysis have together played a critical role in optimization and game theory. It is currently recognized that minimax problems and techniques appear throughout a broad spectrum of disciplines, including game theory, optimization, and computational complexity. Many interesting and sophisticated problems are formulated as minimax applications, as in the fields of combinatorial optimization, scheduling, location, packing, searching, and triangulation. The contributions to this text cover a wide range of topics and provide a clear picture of recent research and developments in minimax theory. It is aimed at graduate students as well as researchers in optimization, computer science, and related areas.

As its title implies, Advances in Multicriteria Analysis presents the most recent developments in multicriteria analysis and in some of its principal areas of application, including marketing, research and development evaluation, financial planning, and medicine. Special attention is paid to the interaction between multicriteria analysis, decision support systems and preference modeling. The five sections of the book cover: methodology; problem structuring; utility assessment; multi-objective optimisation; real world applications. Audience: Researchers and professionals who are operations researchers, management scientists, computer scientists, statisticians, decision analysts, marketing managers and financial analysts.

Optimization problems abound in most fields of science, engineering and technology. In many of these problems it is necessary to compute the global optimum (or a good approximation) of a multivariable function. The variables that define the function to be optimized can be continuous and/or discrete and, in addition, they often have to satisfy certain constraints. Global optimization problems belong to the complexity class of NP-hard problems. Such problems are difficult to solve; traditional descent optimization algorithms based on local information are inadequate for solving them. In most cases of practical interest the number of local optima increases, on the average, exponentially with the size of the problem (number of variables). Furthermore, most of the traditional approaches fail to escape from a local optimum in order to continue the search for the global solution.Global optimization has received a lot of attention in recent years, due to the success of new algorithms for solving large classes of problems from diverse areas such as computational chemistry and biology, structural optimization, computer sciences, operations research, economics, and engineering design and control. This work contains papers presented at the conference on "State of the Art in Global Optimization: Computational Methods and Applications" held at Princeton University, April 28-30, 1995. The conference presented current research on global optimization and related applications in science and engineering. The papers included cover a wide spectrum of approaches for solving global optimization problems and applications.