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MODELS Workshops Scheduler

Quick&dirty (Dijkstra-would-not-have-liked-it) solver for workshop allocation with (i) OC scheduling preferences, (ii) OC/audience overlaps, (iii) room capacity, and (iv) full-day/half-day preferences considered.

  • Step 1: Maximize satisfaction.
  • Step 2: Generate all allocations that meet the maximal satisfaction goal.

Contents

  • modelsws-python.mzn - Model file for Python-based execution.
  • modelsws-nopython.mzn - Model file for manual execution.
  • ws2022.dzn - Data file with the 2022 workshop preferences and resource constraints.

Automated run via Python

  • pip install -r requirements.txt
  • python runner.py

Manual run via MiniZinc IDE

  • Run with solve maximize GOAL; first to find the maximal satisfaction score.
  • Then run with constraint satisfactionRatio >= [score]; %solve satisfy; to generate all equally optimal schedules.

Power by MiniZinc.