Datasets Comparison

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.

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

Computer Science, Personnel Scheduling, Healthcare Research

Creative Commons Attribution 4.0 International

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.

1. Extract the ZIP file 2. Install IBM CPLEX 22.1 (academic license available at ibm.com/academic) and/or Google OR-Tools 9.12 3. Compile Java source code: javac -cp "lib/" -d build src/main/java/com/arp/**/.java 4. Run CPLEX solver on real-world data: java -cp "build;lib/*" -Djava.library.path="" com.arp.solver.CPLEXRunnerV2 data/real-world/layer1 5. Run OR-Tools solver on synthetic instance: java -cp "build;lib/*" -Djava.library.path=lib com.arp.solver.ORToolsRunnerV2 data/synthetic/S_E_01 6. Evaluate manual roster: java -cp "build;lib/*" com.arp.evaluator.ManualRosterEvaluatorV2 1 5 7. Results will be generated in output/cplex/, output/ortools/, and output/manual/ folders

Computer Science, Personnel Scheduling, Healthcare Research

Creative Commons Attribution 4.0 International