Anticipatory Planning for Courier, Express and Parcel Services

Abstract

In recent years, the number of challenges for courier, express and parcel services has grown. Today, service providers deal with dynamic changes and uncertainty. Customers can request service at any point of time in the whole service region. Technologies like Global Positioning Systems allow a more detailed and dynamic routing. Furthermore, historical data can be used to anticipate future events. To tackle the new challenges and to utilize the new resources, we suggest modeling customer locations as spatial random variables. This allows a more detailed and therefore efficient routing and decision making. Nevertheless, it requires more complex methods to anticipate future demands, because the straightforward application of graph theoretical approaches is not possible. For an exemplary problem setting in the Euclidean Plane (EP), we introduce a new anticipatory cost benefit heuristic (CBH). Additionally, we adjust techniques of approximate dynamic programming (ADP) and compare the results of CBH and ADP with a myopic approach and an optimal ex post solution. Here, both ADP and CBH outperform the myopic approach.