Demand management in time-slotted last-mile delivery via dynamic routing with forecast orders
Mohammad Abdollahi, Xinan Yang, Moncef Ilies Nasri, Michael Fairbank
Abstract
In this paper, we propose a partially time-windowed dynamic routing approach with forecast orders to tackle the dynamic pricing problem of attended home delivery, one of the challenging problems in last-mile logistics. The purpose of forecast orders is to find a cost-effective route map for delivery with forecast orders to guide the delivery system to accept real orders in potentially better time slots for servicing. Initially, we build and optimise virtual routes using forecast orders without time windows. Upon the arrival of real orders, we replace the forecast orders with incoming real orders to help the delivery system estimate the opportunity cost of making the delivery in each time slot. Dynamic pricing is then used to influence the customer’s choices of servicing slots, and based on what the customer selects, the real order replaces the forecast order, and the route map is re-optimised. This strategy leads to better scheduling for the overall route map and more slot availability for incoming customers. Through computational study, we demonstrate the benefit of our approach compared to static pricing and previous dynamic pricing policies, with or without forecast orders. In particular, by employing forecast orders without time windows, we witness a decrease in delivery costs and an increase in the number of accepted orders, leading to higher profits.