Design Optimization with MATLAB

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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
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