Amazon Technologies, Inc.

Meghna Singla

Ziyan Huang

Wilko Ziggy Schulz-Mahlendorf

John Schroder

Prashanth Paramanandan

Felipe Lagos

Robert McDonald

Thomas Fillebeen

Joshua Hum

Margaret P Pierson

Embodiments herein describe a predictive delivery planning system that includes a forecaster that predicts simulated orders (e.g., forecasted orders) for multiple different demand scenarios. Once the simulated orders are selected, a route planner can generate routes for delivering the simulated and actual customer orders for each scenario. The planning system then converts these routes in labor plans indicating the amount of time a delivery driver would need to deliver the orders. The planning system identifies a set of labor blocks from the labor plans and determines whether these blocks satisfy a utilization threshold. Put differently, the planning system uses a releasing policy that releases labor blocks whose expected utilization is higher than a predetermined threshold. The released labor blocks are then displayed to delivery drivers who can then select how many of the labor blocks they would like to work.

Predicting demand for route generation

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Seattle, WA, United States of America

Meghna Singla