Joint Dynamic Pricing and Order Fulfillment for E-commerce Retailers

We consider an e-commerce retailer (e-tailer) who sells a catalog of products to customers from different regions during a finite selling season and fulfills orders through multiple fulfillment centers. The e-tailer faces a joint pricing and fulfillment (JPF) optimization problem: at the beginning of each period, the e-tailer needs to jointly decide the price for each product and how to fulfill an incoming order (i.e., from which warehouse to ship the order). The objective of the e-tailer is to maximize its total expected profits defined as total expected revenues minus total expected shipping costs. (All other costs are fixed in this problem.) The exact optimal policy for JPF is difficult to solve; so, we propose two heuristic controls that have provably good performance compared to reasonable benchmarks. Our first heuristic control directly uses the solution of a deterministic approximation of JPF as its control parameters. Our second heuristic control improves the first one by adaptively adjusting the original control parameters according to the realized demand. An important feature of the second heuristic control is that it decouples the real-time pricing and fulfillment decisions, making it easy to implement. We show theoretically and numerically that the second heuristic control significantly outperforms the first heuristic control and is very close to a benchmark that jointly reoptimizes the full deterministic problem at the beginning of every period.