Schedule optimization for a conference

In this project, we optimize a schedule for a conference based on time/room constraints and attendance preferences of the users. This project is only a backend in which the actual solving is done. The interaction with a graphical frontend is done via import/export of json files.

The general workflow is:

1. Read in the constraints from a .json file. The input format is specified on this wiki page.
2. Construct an integer linear program (ILP) from the constraints using PuLP. The ILP formulation is described on this wiki page.
3. Solve the ILP using a solver supported by PuLP, e.g. HiGHS or Gurobi.
4. Output the solution into a .json file. The output format is specified on this wiki page.

Setup

To install this project, simply run

$ pip install git+https://github.com/Die-KoMa/ak-plan-optimierung.git

To run the solver, simply call

$ python -m akplan.solve PATH_TO_JSON_INPUT

For a list of available cli options, run python -m akplan.solve --help.

Development setup

For a development setup, clone this repository and run pip install -e . in the repository directory. Further, install the tool nox.

To see all available nox sessions, run nox --list:

* test -> Run pytest on all test cases.
* fast-test -> Run pytest on fast test cases.
* lint -> Check code conventions.
* typing -> Check type hints.
* format -> Fix common convention problems automatically.
* coverage -> Check test coverage and generate a html report.
* coverage-clean -> Remove the code coverage website.

A session can then be called via nox -s <session_name>.