This book provides a broad introduction to optimization with a focus on practical algorithms for the design of engineering systems. The text is intended for advanced undergraduates and graduate students as well as professionals. The examples are implemented in the Julia programming language.
Topics include:
- Derivatives and gradients.
- Stochastic methods.
- Constrained optimization.
- Sampling plans.
- Optimization under uncertainty.
- Multidisciplinary design optimization.
Textbook: Algorithms for optimization.