EURO 2025 Leeds
Abstract Submission

455. Mixed-integer programming solutions for wellbeing-based scheduling of nurses in acute wards

Invited abstract in session MC-11: Scheduling and queuing in healthcare, stream OR in Healthcare (ORAHS).

Monday, 12:30-14:00
Room: Clarendon SR 1.03

Authors (first author is the speaker)

1. Talia Emmanuel
School of Health Sciences, University of Southampton
2. Carlos Lamas-Fernandez
Southampton Business School, University of Southampton

Abstract

Multiple scheduling goals must be considered during the generation of effective and efficient nurse rosters. These traditionally include achieving staffing level targets, adhering to legal and contractual working time regulations, and mitigating the risks of shift work and night work. Amid ongoing issues with recruitment/retention of health care staff in England, there is now also increased demand to proactively consider nurses’ scheduling needs and wishes. While the Nurse Scheduling Problem (NSP) has been extensively studied, a significant research-to-application gap remains due to inherent challenges in modelling real-world rostering. This paper presents a new mathematical model for nurse scheduling designed to capture real-world shift/staffing configurations and produce ward rosters optimised for nurses’ working time preferences and wellbeing. The model was formulated as a mixed-integer linear program (MILP) that minimised solution values according to constraints limiting the assignment of shifts that contradict nurses’ scheduling needs and/or increase likelihood of sickness absence. Improved schedules were produced across a series of experimental scenarios, including: rostering a team of nurses with varied working hours contracts, rostering 20 randomly generated wards with varied coverage requirements and team sizes, and rostering with customised penalisation of shift assignments depending on the ‘preference profile’ assigned to individual nurses.

Keywords

Status: accepted

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