Engineering Optimization: Theory and Practice

The revised and updated new edition of the popular optimization book for engineers

The thoroughly revised and updated fifth edition of Engineering Optimization: Theory and Practice offers engineers a guide to the important optimization methods that are commonly used in a wide range of industries. The author―a noted expert on the topic―presents both the classical and most recent optimizations approaches. The book introduces the basic methods and includes information on more advanced principles and applications.

The fifth edition presents four new chapters: Solution of Optimization Problems Using MATLAB; Metaheuristic Optimization Methods; Multi-Objective Optimization Methods; and Practical Implementation of Optimization. All of the book's topics are designed to be self-contained units with the concepts described in detail with derivations presented. The author puts the emphasis on computational aspects of optimization and includes design examples and problems representing different areas of engineering. Comprehensive in scope, the book contains solved examples, review questions and problems. This important book:

• Offers an updated edition of the classic work on optimization
• Includes approaches that are appropriate for all branches of engineering
• Contains numerous practical design and engineering examples
• Offers more than 140 illustrative examples, 500 plus references in the literature of engineering optimization, and more than 500 review questions and answers
• Demonstrates the use of MATLAB for solving different types of optimization problems using different techniques

Written for students across all engineering disciplines, the revised edition of Engineering Optimization: Theory and Practice is the comprehensive book that covers the new and recent methods of optimization and reviews the principles and applications.

Singiresu S. Rao is a Professor in the Mechanical and Aerospace Engineering Department at the University of Miami. His main areas of research include multi objective optimization and uncertainty models in engineering analysis, design and optimization.