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+# Optimal student---topic assignment
+
+The script `assignment.py input.toml` calculates **all** optimal student---topic assignments under the assumption
+that the $i$-th topic preference of student $v$ is worth $\approx 2^{-i}$. Then we set up an ILP that maximizes the
+score over all students, adds cutting planes to enumerate all optimal solutions and draws one at random from them.
+
+It is possible to set a seed in the code to ensure the reproducibility of the procedure.
+
+First steps:
+```
+pip install -r requirements.txt
+```
+
+Then: `python assignment.py input.toml`, where `input.toml` has the following format:
+```
+[students]
+a=[1,2,3]
+b=[2,4]
+```
+Here, we have two students `a` and `b`. Student `a` would prefer topic `1` over topic `2` over topic `3`, while student `b` would prefer topic `2` over topic `4`.