An Introduction to Optimization

Praise for the <i>Third Edition</i> «. . . guides and leads the reader through the learning path . . . [e]xamples are stated very clearly and the results are presented with attention to detail.» —MAA Reviews <br /> <br /> Fully updated to reflect new developments in the field, the <i>Fourth Edition</i> of <i>Introduction to Optimization</i> fills the need for accessible treatment of optimization theory and methods with an emphasis on engineering design. Basic definitions and notations are provided in addition to the related fundamental background for linear algebra, geometry, and calculus. <br /> <br /> This new edition explores the essential topics of unconstrained optimization problems, linear programming problems, and nonlinear constrained optimization. The authors also present an optimization perspective on global search methods and include discussions on genetic algorithms, particle swarm optimization, and the simulated annealing algorithm. Featuring an elementary introduction to artificial neural networks, convex optimization, and multi-objective optimization, the <i>Fourth Edition</i> also offers: <br /> <ul> <li>A new chapter on integer programming </li> <li>Expanded coverage of one-dimensional methods </li> <li>Updated and expanded sections on linear matrix inequalities </li> <li>Numerous new exercises at the end of each chapter </li> <li>MATLAB exercises and drill problems to reinforce the discussed theory and algorithms </li> <li>Numerous diagrams and figures that complement the written presentation of key concepts </li> <li>MATLAB M-files for implementation of the discussed theory and algorithms (available via the book's website) </li> </ul> <i>Introduction to Optimization, Fourth Edition</i> is an ideal textbook for courses on optimization theory and methods. In addition, the book is a useful reference for professionals in mathematics, operations research, electrical engineering, economics, statistics, and business.