Design Optimization with MATLAB

 Engineers use design optimization tools to automate finding the best design parameters while satisfying project requirements and to evaluate trade-offs among competing designs. Using these tools results in faster design iterations and allows evaluating a larger number of parameters and alternative designs compared with manual approaches.

We will show how to use apps and functions in Optimization Toolbox and Global Optimization Toolbox to define and solve design optimization problems. Optimization can be applied to design models that are either analytic or black-box including those built with machine learning and simulations. We will use examples from different engineering domains to demonstrate these capabilities.

Highlights

Defining objectives, constraints and design variables

Interactively creating and solving optimization problems with an app

Choosing the best solver for your problem

Setting options to improve results

Using parallel computing to accelerate design studies

Chapters:

00:00 Introduction to design optimization

10:16 Multistage rocket design optimization example

15:50 Current-carrying cables design optimization example

28:26 Electrified powertrain gear ratios design optimization example

41:42 Tips for selecting optimization tools

45:21 Key takeaways