Operational Decision Making in Shared Truckload Transportation

Abstract

The increasing number of gasoline-powered trucks on the road, projected to continue rising, contributes significantly to traffic congestion and carbon emissions. With many trucks partially empty, load consolidation offers a promising solution to these challenges. Shared truckload transportation, an emerging model in long-haul freight, allows freight brokers to reduce costs, lower emissions, and decrease the number of trucks on the road by consolidating shipments. However, this model adds complexity to decision-making tasks like driver assignment and load bundling. This study introduces frameworks that support decision-making for carriers and brokers, aimed at reducing current and future operational costs. We evaluate these frameworks through a computational study based on a Southeast U.S. freight carrier, demonstrating substantial cost reductions and improved operational efficiency.