This app attempts to solve the problem of seating a group of guests at a wedding (or other occasion) so that everyone knows people on their table.
The approach taken involves:
Using a connection matrix that defines the strength of connections between all the guests, and using that to score a given arrangement. Credit for this goes to Meghan L. Bellows and J. D. Luc Peterson2
http://www.improbable.com/news/2012/Optimal-seating-chart.pdf
Using simmulated annealing to attempt to find a good solution.
The code for this comes from https://github.com/perrygeo/python-simulated-annealing
seating_planner/solver.py contains the main entry point for the algorithm
seating_planner/web_app.py contains a Flask web app as a UI, including a relatively nice interface for entering the connection matrix.
Preferably in a virtualenv:
- Add the current directory to the Python path
- $ pip install -r requirements.txt
- ./seating_planner/web_app.py
Access on localhost:5000
It can be run under PyPy for significant speedups (about 5-10x)
It can de deployed using any WSGI container e.g. gunicorn:
$ gunicorn -b 127.0.0.1:12345 -D -w 4 seating_planner.web_app:app
seating_planner/anneal.py has its own copyright licence.
Other code is put into the public domain.