R. Horst – författare

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.

In recent years global optimization has found applications in many interesting areas of science and technology including molecular biology, chemical equilibrium problems, medical imaging and networks. The collection of papers in this book indicates the diverse applicability of global optimization. Furthermore, various algorithmic, theoretical developments and computational studies are presented. Audience: All researchers and students working in mathematical programming.

Global optimization is concerned with the computation and characterization of global optima of nonlinear functions. Global optimization problems are widespread in the mathematical modelling of real world systems for a very broad range of applications. Since the 19070s many new theoretical, algorithmic and computational contributions have helped to solve globally multi-extreme problems arising from important practical applications. This comprehensive textbook covers the fundamentals in global optimization. The second edition includes algorithms, applications, and complexity results for quadratic programming, concave minimization, DC and Lipshitz problems, decomposition algorithms for nonconvex optimization, and nonlinear network flow problems. Each chapter contains illustrative examples and ends with carefully selected exercises, which are designed to help the student to get a grasp of the material and enhance their knowledge of global optimization methods.

Global optimization is concerned with the computation and characterization of global optima of nonlinear functions. Global optimization problems are widespread in the mathematical modelling of real world systems for a very broad range of applications. Since the 19070s many new theoretical, algorithmic and computational contributions have helped to solve globally multi-extreme problems arising from important practical applications. This comprehensive textbook covers the fundamentals in global optimization. The second edition includes algorithms, applications, and complexity results for quadratic programming, concave minimization, DC and Lipshitz problems, decomposition algorithms for nonconvex optimization, and nonlinear network flow problems. Each chapter contains illustrative examples and ends with carefully selected exercises, which are designed to help the student to get a grasp of the material and enhance their knowledge of global optimization methods.

In recent years global optimization has found applications in many interesting areas of science and technology including molecular biology, chemical equilibrium problems, medical imaging and networks. The collection of papers in this book indicates the diverse applicability of global optimization. Furthermore, various algorithmic, theoretical developments and computational studies are presented. Audience: All researchers and students working in mathematical programming.