A labeling method for dynamic driver-task assignment with uncertain task durations

The problem of assigning drivers to cover tasks with service time windows and uncertain task durations is formulated as a dynamic stochastic decision model. We develop an adaptive labeling solution procedure that can incorporate various practical constraints and work rules. Experiments are conducted to evaluate the procedure's performance and compare the stochastic and deterministic formulations.