EURO 2025 Leeds
Abstract Submission

1766. A cluster-based approach to elective surgical planning

Invited abstract in session TB-17: Novel applications in warehousing, maritime transport, and healthcare, stream Combinatorial Optimization.

Tuesday, 10:30-12:00
Room: Esther Simpson 2.08

Authors (first author is the speaker)

1. Ilaria Salvadori
Department of Information Engineering and Mathematics, University of Siena
2. Alessandro Agnetis
Ingegneria dell'Informazione e Scienze Matematiche, Università di Siena
3. Marco Pranzo
Dipartimento di Ingegneria dell'Informazione, Università di Siena

Abstract

Effective scheduling of operating rooms is crucial for optimizing surgical workflows, enhancing patient outcomes, and maximizing healthcare resources utilization. However, despite the huge literature on surgical planning, only a small fraction of all models has been implemented in practice.
This study proposes a new approach to surgical planning that balances surgeon autonomy with efficient resource use. While surgeons value decision-making freedom, managers aim to optimize operating rooms and wards utilization. Consequently, the final plan often results from a negotiation between the parties. Our approach aims at supporting such negotiation, pursuing a compromise between professionals’ preferences and hospital efficiency.
The key idea of our modeling approach is to partition all surgeries into a limited number of surgical groups (clusters), each being relatively homogeneous in terms of resource consumption. Within the framework of a long-term agreed-upon Master Surgical Schedule, our model computes the number of procedures from each cluster to be performed in the next planning period. This ensures efficiency while still allowing surgeons flexibility in patient selection.
We illustrate the model and its validation through a long-term simulation of our decision support tool. Different clustering strategies and objective functions have been implemented, and various performance indicators are observed, allowing a comparison between our approach and the current policy.

Keywords

Status: accepted

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