This undergraduate textbook aims to introduce students of science and engineering to the fascinating field of optimization. It brings together mathematical programming, variational problems, and optimal control, thus giving students an overall view of the subject. Applied mathematicians, physicists, engineers, and scientists will all find this introduction to optimization useful.

From the reviews:

"This is an introductory text on optimization methods written for students of science and engineering. The variety of the different optimization tasks is illustrated in the introductory chapter by several concrete examples. The basic ideas and techniques for solving the different types of optimization problems are motivated by using many examples and illustrations. Hence, this book is suitable for readers who want to get first information about optimization and optimization techniques ." (K. Marti, ZAMM Zeitschrift für Angewandte Mathematik und Mechanik, Vol. 84 (10-11), 2004)

"This book aims at providing undergraduate students and graduate beginners in science and engineering with a general overview of optimization theory. The book is well written and reads easily . Each chapter is followed by a series of exercises, and a selective bibliography . The book will be suitable for a self-study of optimization or to support a general introductory course. It is likely to also serve as a general reference for the audience to whom it is addressed." (Gérard Lebourg, Mathematical Reviews, 2004j)

"The undergraduate textbook introduces students of science and engineering to the field of optimization. It brings together the subfields of mathematical programming, variational calculus, and optimal control, thus giving students an overall view of all aspects of optimization in a single reference. As a primer on optimization, its main goal is to provide a succinct and accessible introduction . There are numerous examples, illustrations, and exercises throughout the text." (Zentralblatt für Didaktik der Mathematik, Mai, 2004)

"This book introduces students of science and engineering to the fascinating field of optimisation. Several features have been united: conciseness and completeness, brevity and clarity . It's a unique book that brings together the subfields thus giving studentsan overall view of all aspects of optimisation . There are numerous examples, illustrations and exercises throughout the text, making it an ideal book for self-study. Applied mathematicians, physicists, engineers and scientists will all find this introduction to optimisation extremely useful." (Gregory Guisbiers, Physicalia, Vol. 57 (3), 2005)

Autorentext

Pablo Pedregal received his Ph.D. degree in Mathematics from the University of Minnesota at the end of 1989, under the guidance of D. Kinderlehrer. Soon after that, he became Associate Professor at U. Complutense. During the academic year 1994-95 he moved to U. de Castilla-La Mancha where he led the Math Department for several years. In 1997 he became full professor. His field of interest focuses on variational techniques applied to optimization in a broad sense, including, but not limited to, calculus of variations-especially vector, non-convex problems-, optimal design in continuous media, optimal control, etc, and more recently he has explored variational ideas in areas like inverse problems, and dynamical systems, as well as optimal control problems governed by hyper-elasticity. He has regularly traveled to research centers in the USA and Europe. He has written more than one hundred research articles, seven specialized books (at least three of them with Springer), and some other of a more didactic style for undergraduates.

Klappentext

This undergraduate textbook introduces students of science and engineering to the fascinating field of optimization. It is a unique book that brings together the subfields of mathematical programming, variational calculus, and optimization in a single reference. As a primer on optimization, its main goal is to provide a succinct and accessible introduction to linear programming, nonlinear programming, numerical optimization algorithms, variational problems, dynamic programming, and optimal control. Prerequisites have been kept to a minimum, although a basic knowledge of calculus, linear algebra, and differential equations is assumed.

There are numerous examples, illustrations, and exercises throughout the text, making it an ideal book for self-study. Applied mathematicians, physicists, engineers, and scientists will find this introduction to optimization extremely useful.

Inhalt
Linear Programming.- Nonlinear Programming.- Approximation Techniques.- Variational Problems and Dynamic Programming.- Optimal Control.