An approximate dynamic programming approach to attended home delivery management

Using real, large-scale industry data, we estimate a demand model including a multinomial logit model of customers' delivery time slot choice, and show in simulation studies that we can improve profits by over two percent in all tested instances relative to using a fixed-price policy commonly encountered in e-commerce. These improvements are achieved despite making strong assumptions in estimating delivery cost. These assumptions allow us to reduce computational run-time to a level suitable for real-time decision making on delivery time slot feasibility and pricing. Our approach provides quantitative insight into the importance of incorporating expected future order displacement costs into opportunity cost estimations alongside marginal delivery costs.