Benchmark Dataset for the Multi-Layer Anaesthetist Rostering Problem
收藏DataCite Commons2026-04-23 更新2026-05-04 收录
下载链接：
https://data.mendeley.com/datasets/rtg2nkbnd9/2
下载链接
链接失效反馈官方服务：
资源简介：
This dataset provides a comprehensive benchmark for the Anaesthetist Rostering Problem (ARP), a multi-layer healthcare workforce scheduling problem involving monthly on-call, weekly daytime, and operating theatre room
assignments. The dataset includes 32 synthetic instances across four sizes (Small, Medium, Large, XLarge) and four difficulty levels (Easy, Medium, Hard, VeryHard), along with 5 months of anonymised real-world operational
data from a Malaysian teaching hospital. The constraint model comprises 8 hard constraints and 21 soft constraints with dual-matrix fairness enforcement, all verified against real-world data with zero hard constraint
violations. Baseline results from IBM CPLEX 22.1 and Google OR-Tools CP-SAT 9.12 are provided for all instances, together with an evaluated manual roster for comparison. Source code for data loading, instance generation,
solver implementation, and manual roster evaluation is included to support reproducibility.
提供机构：
Mendeley Data
创建时间：
2026-04-23
