Benchmark Dataset for the Multi-Layer Anaesthetist Rostering Problem
收藏DataCite Commons2026-04-20 更新2026-05-04 收录
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https://data.mendeley.com/datasets/rtg2nkbnd9/1
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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 30 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, all verified against real-world data with zero hard constraint violations. Baseline results from IBM CPLEX 22.1 are provided for all instances. Source code for data loading, instance generation, and solver implementation is included to support reproducibility.
提供机构：
Mendeley Data
创建时间：
2026-04-20
