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10_optimization_problems [youtube]

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 figures were created using matplotlib and Ipe. The rest is from Wikipedia.
  • Running the Jupyter Notebook requires Python with scientific packages, e.g. the Anaconda distribution. Run it with jupyter notebook.

Repository structure

.
├── 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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Slides and source code for presentation.

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  • Jupyter Notebook 85.5%
  • TeX 14.5%