This repository contains example problems and visualizations of different main flavors in constraint programming and discrete optimization, in general.
Its goal is to show the applicability for classes of problems such as scheduling-like, packing-like, etc. in analogy to what has been successfully done for machine learning (supervised, unsupervised, reinforcement).
Execute the following line (for example in an Anaconda Prompt).
pip install -r requirements.txt
Then enter the directory you're interested in (for example, scheduling) and execute
python run_scheduling.py
An image will appear that visualizes the solution found by MiniZinc.
Each example has an associated .mzn file (and maybe some .dzn data files) and can be executed using the respective run_xyz.py Python file.
Assign tasks without overlaps and precedence requirements.
See https://www.youtube.com/watch?v=2ijSMrOFsJ8 for an explanation of the proposed model.
Fit as many rectangles within a square as possible. See https://www.youtube.com/watch?v=2ijSMrOFsJ8 for an explanation of the proposed model.
Put cars with several options in order such that consecutive capacity constraints are respected on an assembly line.
See https://www.youtube.com/watch?v=2ijSMrOFsJ8 for an explanation of the proposed model.
