SCILAB training course for optimization
You might not be familiar with the numerical concept of optimization, but I am pretty sure your daily work requires you to:
- Build something that is more and more efficient / Increase your profits
- While limiting the production & operation costs / Limiting the associated risk
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| Managers Operational assistance Maximize efficiency, lower costs |
Traders Decision support system Maximize revenue, lower risks |
Engineers Multidisciplinary & robust design optimization / Model Predictive Control |
If you are still reading, I can say: I told you! And what you are currently facing is called an optimization problem: It is all about trying to maximize one or many objectives under given constraints.
Training objective
Provide you with the basics to be able to:
- Recognize what in your daily work is an optimization problem
- Understand some basics on optimization theory and its numerical implementation
- Qualify your porblem to choose the most efficient method to solve it
- Discover different methods implemented in Scilab and make efficient use of it
Training content
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What is optimization used for |
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Numerical setting |
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| Problem qualification Introduction to problem segmentation and problematic of solver efficiency |
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| Algorithms in SCILAB Detailed description of each kind of problem with classic use-cases, and dedicated SCILAB function to solve it. Exercises are provide to learn how to handle those functions |
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| Robust optimization Introduction to the reliability issue and need for robust optimization |
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Training duration
Depending on your mathematical level:
- Beginner (3 days)
We will take 2 days for the theoritical content to be sure you master the basis and one day to explore the exercises - Intermediate (2 to 3 days)
We can take only 1 day for the theoritical content, focus on the exercise on another day. If you are interested in more dedicated Scilab experience, you can also provide us with one of your use case that we will investigate together on one more day.