  Truck platooning is a promising transportation mode in which several trucks
drive together and thus save fuel consumption by suffering less air resistance.
In this paper, we consider a truck platooning system for which we jointly
optimize the truck routes and schedules from the perspective of a central
platform. We improve an existing decomposition-based heuristic by Luo and
Larson (2022), which iteratively solves a routing and scheduling problem, with
a cost modification step after each scheduling run. We propose different
formulations for the routing and the scheduling problem and embed these into
Luo and Larson's framework, and we examine ways to improve their iterative
process. In addition, we propose another scheduling heuristic to deal with
large instances. The computational results show that our procedure achieves
better performance than the existing one under certain realistic settings.
