Navigating uncertainty in Amazon's middle-mile network

Before the "last mile" delivery driver sets off for your home, your Amazon item has moved through the middle-mile network of fulfillment centers and sort centers, which brings products close enough to customers to make our same-day or next-day shipping promises possible. For years, Amazon engineers and scientists have been pushing computational boundaries to optimize this network under uncertainty, and that push has accelerated as the network has grown more complex. What happens when a huge snowstorm closes major highways, a sort center is hit by a power outage, or demand for a viral product spikes? These headline disruptions get attention because they're obvious system shocks that vividly illustrate the challenge of planning for uncertainty. But the most important sources of uncertainty are far more subtle: the day-to-day variations in demand and travel times that, if you don't look closely enough, erode efficiency across the entire network. A snowstorm means two fulfillment centers are operating at reduced capacity, and a sort center is closed, but…