Dynamic Optimization

A snapshot of the central ideas used to control fracture properties of engineered structural metallic materials, Advanced Structural Materials: Properties, Design Optimization, and Applications illust

This book starts with illustrations of the ubiquitous character of optimization, and describes numerical algorithms in a tutorial way. It covers fundamental algorithms as well as more specialized and

This text provides an excellent balance of theory and application that enables you to deploy powerful algorithms, frameworks, and methodologies to solve complex optimization problems in a diverse rang

Optimization is an important tool used in decision science and for the analysis of physical systems used in engineering. One can trace its roots to the Calculus of Variations and the work of Euler and

This reference provides a concise overview of the key principles in dose selection and optimization and demonstrates applicability to recent successful new drug applications. Compiling key issues and

This book aims to demonstrate and detail the pervasive nature of Discrete Optimization. The handbook couples the difficult, critical-thinking aspects of mathematical modeling with the hot area of disc

This title provides a comprehensive survey over the subject of probabilistic combinatorial optimization, discussing probabilistic versions of some of the most paradigmatic combinatorial problems on gr

This is the first book devoted entirely to Particle Swarm Optimization (PSO), which is a non-specific algorithm, similar to evolutionary algorithms, such as taboo search and ant colonies.Since its ori

Optimization is one of the most important areas of modern applied mathematics, with applications in fields from engineering and economics to finance, statistics, management science, and medicine. Whil

This book constitutes the joint refereed proceedings of the 8th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2005 and the 9th International Worksh

It has widely been recognized that submodular functions play essential roles in efficiently solvable combinatorial optimization problems. Since the publication of the 1st edition of this book fifteen

Dynamic games continue to attract strong interest from researchers interested in modelling competitive as well as conflict situations exhibiting an intertemporel aspect. Applications of dynamic games

Tabu Search (TS) and, more recently, Scatter Search (SS) have proved highly effective in solving a wide range of optimization problems, and have had a variety of applications in industry, science, and

Modeling and Control of Dynamic Systems teaches the basic concepts of control systems analysis and design. The book first focuses on understanding the basic building blocks of the dynamic systems surr

There are many highly effective optimization, feedback control, and automation systems embedded in living organisms and nature. Evolution persistently seeks optimal robust designs for biological feedb

The robust capability of Evolutionary Algorithms (EAs) to find solutions to difficult problems has permitted them to become the optimization and search techniques of choice for many practical static p

Many physicists are not aware of the fact that they can solve their problems by applying optimization algorithms. Since the number of such algorithms is steadily increasing, many new algorithms have n

Optimization is concerned with finding the best (optimal) solution to mathematical problems that may arise in economics, engineering, the social sciences and the mathematical sciences. As is suggested by its title, this book surveys various ways of penetrating the subject. The author begins with a selection of the type of problem to which optimization can be applied and the remainder of the book develops the theory, mainly from the viewpoint of mathematical programming. To prevent the treatment becoming too abstract, subjects which may be considered 'unpractical' are not touched upon. The author gives plausible reasons, without forsaking rigor, to show how the subject develops 'naturally'. Professor Ponstein has provided a concise account of optimization which should be readily accessible to anyone with a basic understanding of topology and functional analysis. Advanced students and professionals concerned with operations research, optimal control and mathematical programming will welc

This book presents the up-to-date research developments in economics, management and optimization applied to sports, which would be of interest to researchers and practitioners in sports industry, and

A First Course in Combinatorial Optimization is a text for a one-semester introductory graduate-level course for students of operations research, mathematics, and computer science. It is a self-contained treatment of the subject, requiring only some mathematical maturity. Topics include: linear and integer programming, polytopes, matroids and matroid optimization, shortest paths, and network flows. Central to the exposition is the polyhedral viewpoint, which is the key principle underlying the successful integer-programming approach to combinatorial-optimization problems. Another key unifying topic is matroids. The author does not dwell on data structures and implementation details, preferring to focus on the key mathematical ideas that lead to useful models and algorithms. Problems and exercises are included throughout as well as references for further study.

A First Course in Combinatorial Optimization is a text for a one-semester introductory graduate-level course for students of operations research, mathematics, and computer science. It is a self-contained treatment of the subject, requiring only some mathematical maturity. Topics include: linear and integer programming, polytopes, matroids and matroid optimization, shortest paths, and network flows. Central to the exposition is the polyhedral viewpoint, which is the key principle underlying the successful integer-programming approach to combinatorial-optimization problems. Another key unifying topic is matroids. The author does not dwell on data structures and implementation details, preferring to focus on the key mathematical ideas that lead to useful models and algorithms. Problems and exercises are included throughout as well as references for further study.

This is the first elementary exposition of the main ideas of complexity theory for convex optimization. Up to now, most of the material can be found only in special journals and research monographs.

Schedule-Based Dynamic Transit Modeling: Theory and Applications outlines the new schedule-based dynamic approach to mass transit modeling. In the last ten years the schedule-based dynamic approach ha

This text offers many multiobjective optimization methods accompanied by analytical examples, and it treats problems not only in engineering but also operations research and management. It explains ho

Employing a closed set-theoretic foundation for interval computations, Global Optimization Using Interval Analysis simplifies algorithm construction and increases generality of interval arithmetic. Th

Today's need-to-know optimization techniques, at your fingertips The use of optimization methods is familiar territory to academicians and researchers. Yet, in today's world of deregulated electri

Detailed mathematical models are increasingly being used by companies to gain competitive advantage through such applications as model-based process design, control and optimization. Thus, building va

The aim of this volume is to show how Fuzzy Sets and Systems can help to provide robust and adaptive heuristic optimization algorithms in a variety of situations. The book presents the state of the ar

In the past three decades, local search has grown from a simple heuristic idea into a mature field of research in combinatorial optimization that is attracting ever-increasing attention. Local search

This book is the first to be devoted to multi-state system (MSS) reliability analysis and optimization. It contains a brief historical overview, presents the basic concepts of MSS, defines MSS reliabi

A unique interdisciplinary foundation for real-world problem solvingStochastic search and optimization techniques are used in a vast number of areas, including aerospace, medicine, transportation, and

Large-scale optimization is becoming increasingly important for students and professionals in electrical and industrial engineering, computer science, management science and operations research, and a

The topology optimization method solves the basic enginee- ring problem of distributing a limited amount of material in a design space. The first edition of this book has become the standard text on o

This systematic and comprehensive account of asymptotic sets and functions develops a broad and useful theory in the areas of optimization and variational inequalities. The central focus is on problem

This reference provides a guide for applications specialists to the most important instruments and the major recent advances in the field of applied optimization. Pardalos (industrial and systems eng

Important text examines algorithms for optimizing large systems and clarifying relations between optimization procedures. Much data appear as charts and graphs and will be highly valuable to readers i

Dynamic Models of Oligopoly

The goal of this book is to present and evaluate the concept of dynamic testing. Unlike 'static' tests such as the SAT or IQ tests, dynamic testing emphasizes learning potential rather than past learning accomplishments. The book opens with a theoretical framework of abilities as forms of developing expertise. It then continues with an introduction to dynamic testing and then a capsule history of dynamic testing. The book also reviews the approaches of Feuerstein and Budoff and other diverse approaches to dynamic testing. The Drs Sternberg and Grigorenko present their own three-prong approach to dynamic testing along with two case studies using dynamic testing in their own research. The authors conclude that dynamic testing has enormous potential which has not yet been tapped.

The goal of this book is to present and evaluate the concept of dynamic testing. Unlike 'static' tests such as the SAT or IQ tests, dynamic testing emphasizes learning potential rather than past learning accomplishments. The book opens with a theoretical framework of abilities as forms of developing expertise. It then continues with an introduction to dynamic testing and then a capsule history of dynamic testing. The book also reviews the approaches of Feuerstein and Budoff and other diverse approaches to dynamic testing. The Drs Sternberg and Grigorenko present their own three-prong approach to dynamic testing along with two case studies using dynamic testing in their own research. The authors conclude that dynamic testing has enormous potential which has not yet been tapped.

Evolutionary algorithms are relatively new, but very powerful techniques used to find solutions to many real-world search and optimization problems. Many of these problems have multiple objectives, wh