The ASP-based Nurse Scheduling System at the University of Yamanashi Hospital
Hidetomo Nabeshima, Mutsunori Banbara, Torsten Schaub, Takehide Soh
TL;DR
This work presents a real-world ASP-based solution to the Nurse Scheduling Problem (NSP) at the University of Yamanashi Hospital, balancing hard constraints $H_1$–$H_9$ and soft constraints $S_1$–$S_9$ to align nurse preferences with ward staffing. The scheduling engine, aspital, provides automatic generation via clingo and supports targeted manual adjustments, with a penalty-based objective and a soften_hard mechanism for feasible rescheduling when needed. A key contribution is the use of Large Neighborhood Prioritized Search (LNPS) to enable interactive schedule modification, contrasting with traditional MP approaches. Experimental results show LNPS achieves faster improvements with fewer modifications in short runs while maintaining competitive objective values in longer runs, demonstrating strong practical potential for real-time clinical staffing in six wards, aided by ongoing nurse feedback to refine modeling such as rest-day adjacency and workload balance.
Abstract
We present the design principles of a nurse scheduling system built using Answer Set Programming (ASP) and successfully deployed at the University of Yamanashi Hospital. Nurse scheduling is a complex optimization problem requiring the reconciliation of individual nurse preferences with hospital staffing needs across various wards. This involves balancing hard and soft constraints and the flexibility of interactive adjustments. While extensively studied in academia, real-world nurse scheduling presents unique challenges that go beyond typical benchmark problems and competitions. This paper details the practical application of ASP to address these challenges at the University of Yamanashi Hospital, focusing on the insights gained and the advancements in ASP technology necessary to effectively manage the complexities of real-world deployment.