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

618.62Objective ValueSQF+Nearest
398.3168455.5109512.705569.8991May 5, 2026

Evaluation results

MethodLinks
SQF+NearestAllocation Heuristic=SQF, Scheduling Strategy=Nearest2026.05618.62259.910.6
SQF+TSPAllocation Heuristic=SQF, Scheduling Strategy=TSP2026.05614.88242.290.62
WLB+EarliestAllocation Heuristic=WLB, Scheduling Strategy=Earliest2026.05606.33257.180.73
SQF+EarliestAllocation Heuristic=SQF, Scheduling Strategy=Earliest2026.05604.61242.270.6
SQF+PSMDRLAllocation Heuristic=SQF, Scheduling Strategy=PSMDRL2026.05550.59218.332.5
JOTPMethod Type=Joint Optimization2026.05528.69205.280.95
WLB+TSPAllocation Heuristic=WLB, Scheduling Strategy=TSP2026.05520.75204.660.89
WLB+NearestAllocation Heuristic=WLB, Scheduling Strategy=Nearest2026.05494.19201.410.63
WLB+PSMDRLAllocation Heuristic=WLB, Scheduling Strategy=PSMDRL2026.05480.92222.282.4
SABSMethod Type=Joint Optimization2026.05465.05192.741
OR Tools+EarliestAllocation Heuristic=OR Tools, Scheduling Strategy=Earliest2026.05449.13204.981
OR Tools+TSPAllocation Heuristic=OR Tools, Scheduling Strategy=TSP2026.05416.62185.661
OR Tools+NearestAllocation Heuristic=OR Tools, Scheduling Strategy=Nearest2026.05414.06184.51
SOARMethod Type=Joint Optimization2026.05406.79152.035.06