A hybrid solution approach for the Integrated Healthcare Timetabling Competition 2024

Daniela Guericke; Rolf van der Hulst; Asal Karimpour; Ieke Schrader; Matthias Walter

doi:10.1016/j.ordal.2026.200502

A hybrid solution approach for the Integrated Healthcare Timetabling Competition 2024

Daniela Guericke
, Rolf van der Hulst
, Asal Karimpour
, Ieke Schrader
, Matthias Walter^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

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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 runtime and an extended runtime. Additionally, we investigate the performance of different soft constraints and specific parts of the algorithm. Finally, we highlight open problems and future research directions for further improving the approach.

Original language	English
Article number	200502
Number of pages	18
Journal	Operations Research, Data Analytics and Logistics
Volume	46
Early online date	12 May 2026
DOIs	https://doi.org/10.1016/j.ordal.2026.200502
Publication status	Published - Jun 2026

Keywords

UT-Hybrid-D
Integrated planning
Nurse assignment
Patient admission
Healthcare
Room assignment

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10.1016/j.ordal.2026.200502Licence: CC BY

ArticleFinal published version, 2.11 MBLicence: CC BY

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A hybrid solution approach for the Integrated Healthcare Timetabling Competition 2024
Guericke, D., van der Hulst, R., Karimpour, A., Schrader, I. & Walter, M., 23 Oct 2025, ArXiv.org, 23 p.
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title = "A hybrid solution approach for the Integrated Healthcare Timetabling Competition 2024",

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 runtime and an extended runtime. Additionally, we investigate the performance of different soft constraints and specific parts of the algorithm. Finally, we highlight open problems and future research directions for further improving the approach.",

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note = "{\textcopyright} 2026 The Authors.",

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month = jun,

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journal = "Operations Research, Data Analytics and Logistics",

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AU - Walter, Matthias

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N2 - 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 runtime and an extended runtime. Additionally, we investigate the performance of different soft constraints and specific parts of the algorithm. Finally, we highlight open problems and future research directions for further improving the approach.

AB - 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 runtime and an extended runtime. Additionally, we investigate the performance of different soft constraints and specific parts of the algorithm. Finally, we highlight open problems and future research directions for further improving the approach.

KW - UT-Hybrid-D

KW - Integrated planning

KW - Nurse assignment

KW - Patient admission

KW - Healthcare

KW - Room assignment

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DO - 10.1016/j.ordal.2026.200502

M3 - Article

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JO - Operations Research, Data Analytics and Logistics

JF - Operations Research, Data Analytics and Logistics

M1 - 200502

ER -

A hybrid solution approach for the Integrated Healthcare Timetabling Competition 2024

Abstract

Keywords

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A hybrid solution approach for the Integrated Healthcare Timetabling Competition 2024

Cite this