Near real-time loadplan adjustments for less-than-truckload carriers

Abstract

We design and implement decision support technology to assist dispatchers in the daily management of loadplans in less-than-truckload service networks. The freight volume that enters a service network on the day of operations deviates from the forecast freight volume used to create the loadplan. These deviations cause inefficiencies when the capacity on planned freight paths is no longer sufficient and delays result in missed service promises. Near real-time loadplan adjustments, i.e., rerouting freight on alternate paths, can improve on-time performance without incurring additional cost (e.g., without purchasing additional capacity). The problem of identifying effective alternate freight paths is modeled on a time-expanded network and computationally efficient heuristics are developed for its solution in order to ensure that there is sufficient time to put the adjusted loadplan in place. We demonstrate the practical viability and value of these heuristics in a computational study using real-life data from a large LTL carrier. The results show that on-time performance can be improved without increasing cost, i.e., by rerouting freight and using existing capacity in the service network.