10_optimization_problems

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10_optimization_problems

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Slides and source code for presentation.

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// repository documentation

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# 10_optimization_problems [[youtube](https://www.youtube.com/watch?v=sJ5HTi70wXo)]
Slides and source code (LaTeX and Python) for a presentation.

### Speed dates with optimization problems - 10 problems in 10 minutes

- Efficient algorithm exist for many problems.
- Implementations of these algorithms are also available.
- The remaining difficulty is often having enough prior knowledge to recognize a problem.

## Software used

- The LaTeX file is compiled with `xelatex`.
  - The fonts used are [Open Sans](https://www.fontsquirrel.com/fonts/open-sans) and [Ubuntu Mono](https://www.fontsquirrel.com/fonts/ubuntu-mono).
- The figures were created using [matplotlib](https://matplotlib.org/) and [Ipe](http://ipe.otfried.org/). The rest is from Wikipedia.
- Running the Jupyter Notebook requires Python with scientific packages, e.g. the [Anaconda](https://www.anaconda.com/distribution/) distribution. Run it with `jupyter notebook`.

## Repository structure

```text
.
├── 10_optimization_problems.pdf          <- Presentation
├── 10_optimization_problems.tex          <- Presentation source
├── figs
│   ├── 10_optimization_problems.ipynb    <- Python code
│   └── <figures>                         
├── LICENSE
└── README.md
```

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