Benchmark Dataset for the Multi-Layer Anaesthetist Rostering Problem
Description
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.
Files
Steps to reproduce
1. Extract the ZIP file 2. Install IBM CPLEX 22.1 (academic license available at ibm.com/academic) 3. Compile Java source code: javac -cp "lib/*" -d build src/main/java/com/arp/**/*.java 4. Run solver on real-world data: java -cp "build;lib/*" -Djava.library.path="<CPLEX_BIN_PATH>" com.arp.solver.CPLEXRunnerV2 data_real-world/layer1 5. Run solver on synthetic instance: java -cp "build;lib/*" -Djava.library.path="<CPLEX_BIN_PATH>" com.arp.solver.CPLEXRunnerV2 data_synthetic/S_E_01 6. Results will be generated in output/cplex/ folder 7. To regenerate synthetic instances: java -cp "build;lib/*" com.arp.data.SyntheticGeneratorV6 data_synthetic
Institutions
- National University of MalaysiaSelangor, Bangi