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 fonts used are Open Sans and Ubuntu Mono.
• 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