69. The Integrated Healthcare Timetabling Competition 2024 (IHTC-2024)
Invited abstract in session TC-2: Integrated planning, stream Sessions.
Tuesday, 13:30-15:00Room: NTNU, Realfagbygget R8
Authors (first author is the speaker)
| 1. | Sara Ceschia
|
| Polytechnic Department of Engineering and Architecture, University of Udine | |
| 2. | Roberto Maria Rosati
|
| WU Vienna University of Economics and Business | |
| 3. | Andrea Schaerf
|
| Polytechnic Department of Engineering and Architecture, University of Udine | |
| 4. | Pieter Smet
|
| Computer Science, KU Leuven | |
| 5. | Greet Vanden Berghe
|
| Computer Science, KU Leuven | |
| 6. | Eugenia Zanazzo
|
| Polytechnic Department of Engineering and Architecture, University of Udine |
Abstract
We launched the Integrated Healthcare Timetabling Competition (IHTC-2024, https://ihtc2024.github.io/) to stimulate research on the specifics of integrated scheduling problems in healthcare.
We introduced the Integrated Healthcare Timetabling Problem (IHTP), which brings together three critical problems in healthcare: surgical case planning, patient admission scheduling, and nurse-to-room assignment. In particular, it requires the following decisions: (i) the admission date for each patient (or admission postponement to the next scheduling period), (ii) the room for each admitted patient for the duration of their stay, (iii) the nurse for each room during each shift of the scheduling period, and (iv) the operating theatre for each admitted patient.
We provided a public dataset composed of 30 instances in JSON format, along with the solution checker (in C++) that certifies the quality of a given solution.
We received 32 submissions from teams across various countries around the world. In the first stage of the competition, we selected five finalists from all the participants whose solution methods were evaluated on the hidden dataset on our machine in the second stage. In this talk, we will present the competition results and the general insights we gained about the competition, the problem, and the solution methods.
Keywords
- Optimization algorithms
- Integrated planning of health services
- Benchmarking
Status: accepted
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