A hybrid solution approach for the Integrated Healthcare Timetabling Competition 2024
This work addresses healthcare scheduling optimization for competition participants, representing an incremental improvement through hybrid methods.
The authors tackled the Integrated Healthcare Timetabling Competition 2024 problem by developing a hybrid algorithm combining mixed-integer programming, constraint programming, and simulated annealing in a 3-phase decomposition approach, which achieved third place in the competition and provided new lower bounds for benchmark instances.
We report about the algorithm, implementation and results submitted to the Integrated Healthcare Timetabling Competition 2024 by Team Twente, which scored third in the competition. Our approach combines mixed-integer programming, constraint programming and simulated annealing in a 3-phase solution approach based on decomposition into subproblems. Next to describing our approach and describing our design decisions, we share our insights and, for the first time, lower bounds on the optimal solution values for the benchmark instances. We finally highlight open problems for which we think that addressing them could improve our approach even further.