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RMFS Order Allocation and Robot Scheduling on Real-world Large (test)

828.44Objective ValueSOAR
798.1461,002.63051,207.1151,411.5995May 5, 2026

Evaluation results

MethodLinks
SOARMethod Type=Joint Optimization2026.05828.44275.6816.34
WLB+NearestAllocation Heuristic=WLB, Scheduling Strategy=Nearest2026.05916.77315.232.07
WLB+PSMDRLAllocation Heuristic=WLB, Scheduling Strategy=PSMDRL2026.05926.9347.266.28
WLB+TSPAllocation Heuristic=WLB, Scheduling Strategy=TSP2026.05940.63481
SABSMethod Type=Joint Optimization2026.05978.12329.748
JOTPMethod Type=Joint Optimization2026.051,001.95332.73.64
OR Tools+TSPAllocation Heuristic=OR Tools, Scheduling Strategy=TSP2026.051,178.07426.117
OR Tools+NearestAllocation Heuristic=OR Tools, Scheduling Strategy=Nearest2026.051,229.56447.287
OR Tools+EarliestAllocation Heuristic=OR Tools, Scheduling Strategy=Earliest2026.051,245.25505.757
SQF+PSMDRLAllocation Heuristic=SQF, Scheduling Strategy=PSMDRL2026.051,265.79580.38.19
WLB+EarliestAllocation Heuristic=WLB, Scheduling Strategy=Earliest2026.051,377.31587.612.3
SQF+NearestAllocation Heuristic=SQF, Scheduling Strategy=Nearest2026.051,445.08611.811.64
SQF+TSPAllocation Heuristic=SQF, Scheduling Strategy=TSP2026.051,533.2649.671.9
SQF+EarliestAllocation Heuristic=SQF, Scheduling Strategy=Earliest2026.051,585.79675.221.62