An online ILP-based tool for surgery scheduling and re-scheduling

Abstract Effective management of operating rooms ( ORs ) is a challenging yet crucial aspect of ensuring the proper functioning of hospitals. One of the critical issues in ORs management is developing an efficient surgery schedule. This challenge is known in scientific literature as part of the broader Integrated Operating Room Planning and Scheduling ( IORPS ). In its more general form, the IORPS involves making decisions about when and where surgeries should take place, considering various operational issues and constraints, such as resource utilization, patient priority, surgeon and equipment availability, and possible variations in conditions. This work addresses the specific IORPS faced by a hospital in Naples, aiming to balance two contrasting objectives throughout the planning horizon: maximizing OR utilization and accommodating unforeseeable events, such as variations in surgery durations and emergency arrivals. To address these challenges, we propose a two-phases optimization approach. Phase I focuses on designing an efficient and proactive surgery schedule that maximizes ORs utilization while ensuring an adequate responsiveness to unforeseeable events. Phase II reacts to these events, minimizing deviations from the schedule established in Phase I and remaining efficient and responsive throughout the planning horizon. Both phases are developed in an Integer Linear Programming fashion and integrated into an optimization tool. The effectiveness and performance of the proposed approach are validated using real data provided by the hospital. Experimental results demonstrate that our approach could be a valuable resource for supporting surgery department executives.

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Publication Details

Journal
Soft Computing
Published
2026-02-18
DOI
https://doi.org/10.1007/s00500-025-10845-z
Primary Topic
Healthcare Operations and Scheduling Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

An online ILP-based tool for surgery scheduling and re-scheduling

Maurizio Boccia, Andrea Mancuso, Adriano Masone, Claudio Sterle
Soft Computing
Healthcare Operations and Scheduling Optimization
article

An online ILP-based tool for surgery scheduling and re-scheduling

Maurizio Boccia, Andrea Mancuso, Adriano Masone, Claudio Sterle
article en

Abstract

Abstract Effective management of operating rooms ( ORs ) is a challenging yet crucial aspect of ensuring the proper functioning of hospitals. One of the critical issues in ORs management is developing an efficient surgery schedule. This challenge is known in scientific literature as part of the broader Integrated Operating Room Planning and Scheduling ( IORPS ). In its more general form, the IORPS involves making decisions about when and where surgeries should take place, considering various operational issues and constraints, such as resource utilization, patient priority, surgeon and equipment availability, and possible variations in conditions. This work addresses the specific IORPS faced by a hospital in Naples, aiming to balance two contrasting objectives throughout the planning horizon: maximizing OR utilization and accommodating unforeseeable events, such as variations in surgery durations and emergency arrivals. To address these challenges, we propose a two-phases optimization approach. Phase I focuses on designing an efficient and proactive surgery schedule that maximizes ORs utilization while ensuring an adequate responsiveness to unforeseeable events. Phase II reacts to these events, minimizing deviations from the schedule established in Phase I and remaining efficient and responsive throughout the planning horizon. Both phases are developed in an Integer Linear Programming fashion and integrated into an optimization tool. The effectiveness and performance of the proposed approach are validated using real data provided by the hospital. Experimental results demonstrate that our approach could be a valuable resource for supporting surgery department executives.

Soft ComputingVol. 30(3)
Institute for Systems Analysis (RU), Federico II University Hospital (IT), University of Naples Federico II (IT)
Università degli Studi di Napoli Federico II
Openalex Percentile: Top 58%
Healthcare Operations and Scheduling Optimization
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