Engineering Design Optimization

A rigorous yet accessible graduate textbook covering both fundamental and advanced optimization theory and algorithms.

Joaquim R. R. A. Martins (Author), Andrew Ning (Author)

9781108833417, Cambridge University Press

Hardback, published 18 November 2021

650 pages
25.3 x 19.4 x 2.8 cm, 1.55 kg

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.

1. Introduction
2. A short history of optimization
3. Numerical models and solvers
4. Unconstrained gradient-based optimization
5. Constrained gradient-based optimization
6. Computing derivatives
7. Gradient-free optimization
8. Discrete optimization
9. Multiobjective optimization
10. Surrogate-based optimization
11. Convex optimization
12. Optimization under uncertainity
13. Multidisciplinary design optimization
A. Mathematics background
B. Linear solvers
C. Quasi-Newton methods
D. Test problems.

Subject Areas: Aerospace & aviation technology [TRP], Civil engineering, surveying & building [TN], Automatic control engineering [TJFM], Mechanical engineering [TGB], Technical design [TBD], Optimization [PBU]