Redistricting optimization on Iowa Census data 99 counties 2000
7,089Minimum ValueGenetic Algorithm
Evaluation Results
| Method | Links | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Genetic AlgorithmOptimization Objective=PopDev Only, Number of Runs=1000 Runs2026.04 | 7,089 | 33,133 | 56,705 | 74,159 | 93,313 | 120,914 | 198,058 | 36,608 | 26,745 | 1.8 | |
| Greedy*Method Type=Trajectory-based, Approach enhancement=Combined with our approach, Optimization Objective=PopDev Only, Number of Runs=1000 Runs2026.04 | 755 | 1,939 | 4,239 | 7,523 | 12,779 | 33,193 | 617,469 | 8,540 | 39,796 | 0.002 | |
| GreedyMethod Type=Trajectory-based, Approach enhancement=Standard, Optimization Objective=PopDev Only, Number of Runs=1000 Runs2026.04 | 713 | 2,945 | 7,375 | 13,461 | 33,883 | 343,865 | 1,271,207 | 26,508 | 147,434 | 0.002 | |
| K–LMethod Type=Trajectory-based, Approach enhancement=Standard, Optimization Objective=PopDev Only, Number of Runs=1000 Runs2026.04 | 205 | 807 | 1,703 | 2,627 | 4,593 | 10,079 | 84,301 | 2,890 | 6,050 | 0.02 | |
| K–L*Method Type=Trajectory-based, Approach enhancement=Combined with our approach, Optimization Objective=PopDev Only, Number of Runs=1000 Runs2026.04 | 159 | 459 | 915 | 1,401 | 2,289 | 4,735 | 20,837 | 1,374 | 1,794 | 0.02 | |
| TabuMethod Type=Trajectory-based, Approach enhancement=Standard, Optimization Objective=PopDev Only, Number of Runs=1000 Runs2026.04 | 77 | 223 | 417 | 629 | 1,025 | 3,571 | 62,707 | 608 | 3,332 | 0.05 | |
| Tabu*Method Type=Trajectory-based, Approach enhancement=Combined with our approach, Optimization Objective=PopDev Only, Number of Runs=1000 Runs2026.04 | 33 | 167 | 289 | 371 | 481 | 775 | 5,997 | 192 | 316 | 0.08 |