An MILP-based Lexicographic Approach for Robust Selective Full Truckload Vehicle Routing Problem

Full truckload (FTL) shipment is one of the largest trucking modes. It is an essential part of the transportation industry, where the carriers are required to move FTL transportation demands (orders) at a minimal cost between pairs of locations using a certain number of trucks available at the depots. The drivers who pick up and deliver these orders must return to their home depots within a given time. In practice, satisfying those orders within a given time frame (e.g., one day) could be impossible while adhering to all operational constraints. As a result, the investigated problem is distinguished by the selective aspect, in which only a subset of transportation demands is serviced. Furthermore, travel times between nodes can be uncertain and vary depending on various possible scenarios. The robustness subsequently consists of identifying a feasible solution in all scenarios. Therefore, this study introduces an MILP-based lexicographic approach to solve a robust selective full truckload vehicle routing problem (RSFTVRP). We demonstrated the proposed method’s efficiency through experimental results on newly generated instances for the considered problem.