Bi-objective Hospital Bed Assignment Problem in Emergencies

Hela Jedidi; Hajer Ben-Romdhane; Issam Nouaouri; Saoussen Krichen

doi:10.2991/978-94-6463-654-3_11

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Bi-objective Hospital Bed Assignment Problem in Emergencies

Authors

Hela Jedidi¹^{, *}, Hajer Ben-Romdhane¹, Issam Nouaouri², Saoussen Krichen¹

¹Université de Tunis, Institut Superieur de Gestion de Tunis, LARODEC laboratory, Tunis, Tunisia

²Université de l’Artois, UR 3926, LGI2A laboratory, Bethune, 62400, France

^*Corresponding author. Email: hela.jedidi@esprit.tn

Corresponding Author

Hela Jedidi

Available Online 24 February 2025.

DOI: 10.2991/978-94-6463-654-3_11 How to use a DOI?
Keywords: Emergencies; hospital allocation; optimization; patient allocation; bed assignment
Abstract: During emergencies and pandemics, such as COVID-19 or Mpox, the massive demand for critical resources, including hospital beds, has significantly challenged healthcare systems. Reducing the pressure on these systems is crucial and requires an efficient strategy for patient allocation. This paper proposes a bi-objective optimization model to allocate patients to hospital beds during emergencies, including pandemics. The problem is formulated as a linear programming model. The first objective is to minimize the cost of transporting patients to the nearest hospitals, while the second objective is to minimize the cost of assigning patients to available beds, guaranteeing that bed capacity is fully utilized. We applied the weighted-sum method to combine objectives into a single-objective instance to solve this problem. We tested the proposed model using benchmarks from the literature with IBM Cplex Studio. The findings provide healthcare analysts with valuable insights for creating flexible and effective allocation plans during pandemics.
Copyright: © 2025 The Author(s)
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of the International Conference on Decision Aid and Artificial Intelligence (ICODAI 2024)
Series: Atlantis Highlights in Intelligent Systems
Publication Date: 24 February 2025
ISBN: 978-94-6463-654-3
ISSN: 2589-4919
DOI: 10.2991/978-94-6463-654-3_11 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - Hela Jedidi
AU  - Hajer Ben-Romdhane
AU  - Issam Nouaouri
AU  - Saoussen Krichen
PY  - 2025
DA  - 2025/02/24
TI  - Bi-objective Hospital Bed Assignment Problem in Emergencies
BT  - Proceedings of the  International Conference on Decision Aid and Artificial Intelligence (ICODAI 2024)
PB  - Atlantis Press
SP  - 136
EP  - 146
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-654-3_11
DO  - 10.2991/978-94-6463-654-3_11
ID  - Jedidi2025
ER  -

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