A hybrid solution approach for the Integrated Healthcare Timetabling Competition 2024

TL;DR

This paper details a hybrid solution combining optimization techniques for healthcare timetabling, achieving third place in the 2024 competition and providing new insights and bounds on solution quality.

Contribution

It introduces a novel 3-phase hybrid approach integrating mixed-integer programming, constraint programming, and simulated annealing, with new bounds and analysis for healthcare timetabling.

Findings

Ranked third in the competition

Provided lower bounds on optimal solutions

Analyzed solution quality and constraints

Abstract

In this work, we present the solution approach for the Integrated Healthcare Timetabling Competition 2024 submitted by Team Twente, which ultimately ranked third among the finalists. Our approach combines mixed-integer programming, constraint programming, and simulated annealing in a 3-phase solution approach based on decomposition into subproblems. In addition to describing our approach and design decisions, we share our insights and, for the first time, lower bounds on the optimal solution values for the benchmark instances. We analyze the results based on solution quality for the competition and an extended runtime Additionally, we investigate the different soft constraints and specific parts of the algorithm. Finally, we highlight open problems and future research directions for further improving the approach.