Based on course-tested material, this rigorous yet accessible graduate textbook covers both fundamental and advanced optimization theory and algorithms. It covers a wide range of numerical methods and topics, including both gradient-based and gradient-free algorithms, multidisciplinary design optimization, and uncertainty, with instruction on how to determine which algorithm should be used for a given application. It also provides an overview of models and how to prepare them for use with numerical optimization, including derivative computation. Over 400 high-quality visualizations and numerous examples facilitate understanding of the theory, and practical tips address common issues encountered in practical engineering design optimization and how to address them. Numerous end-of-chapter homework problems, progressing in difficulty, help put knowledge into practice. Accompanied online by a solutions manual for instructors and source code for problems, this is ideal for a one- or two-semester graduate course on optimization in aerospace, civil, mechanical, electrical, and chemical engineering departments.

Author: Joaquim R. R. a. Martins, Andrew Ning
Binding Type: Hardcover
Publisher: Cambridge University Press
Published: 01/20/2022
Pages: 650
Weight: 3.4lbs
Size: 9.80h x 8.40w x 1.10d
ISBN: 9781108833417

About the Author
Ning, Andrew: - Andrew Ning is an Associate Professor of Mechanical Engineering at Brigham Young University, and has previously worked at the National Renewable Energy Laboratory (NREL) as a Senior Engineer.Martins, Joaquim R. R. a.: - Joaquim R. R. A. Martins is a Professor of Aerospace Engineering at the University of Michigan. He is a fellow of the American Institute for Aeronautics and Astronautics, and the Royal Aeronautical Society.