Document Type
Technical Report
Publication Date
5-1-2024
Keywords
Congestion reduction, cargo consolidation, minimizing vehicle trips
Digital Object Identifier (DOI)
https://doi.org/10.5038/CUTR-NICR-Y3-2-7
Abstract
Commercial heavy vehicles, given their frequency of acceleration and deceleration, impact the traffic stream more than passenger cars, leading to greater congestion on the roads. Mixed-cargo shipments, or cargo consolidation, is an operational strategy that has gained traction in many industries because it reduces transportation costs while increasing asset utilization, such as making use of all the available capacity. This practice achieves cost reductions and increased asset efficiency by reducing the number of trips that are needed to deliver the same volume of products among different companies. However, its implementation is far from optimal since it is often carried out by intuition and rudimentary operations, leaving substantial opportunity for process improvements. As part of this project, both a survey and interviews were conducted to understand the industry cargo shipment practices, with responses favoring the use of cargo consolidation adoption. This work developed a methodology to optimize the consolidation of cargo, the routing of shipments of commercial heavy vehicles, the location of logistics distribution centers (namely depots) to minimize distance, and the number of commercial heavy vehicle trips, while also increasing the utilization of transportation assets such as commercial heavy vehicles. This optimization methodology delivers positive impacts on traffic congestion with the reduction of distance traveled and decrease in the number of commercial heavy vehicle trips, which translates to fewer vehicle miles (kilometers) traveled. The methodology was tested using publicly available data pertaining to real-world private-sector operations.
Scholar Commons Citation
Monsreal, Mario M.; Ozkul, Seckin; Prieto, Bill; Rivera, Jose; and Eisele, William, "Cargo Consolidation, Routing, and Location Optimization to Reduce Traffic Congestion by Minimizing Commercial Heavy Vehicle Trips" (2024). Research Reports. 36.
https://digitalcommons.usf.edu/cutr_nicr/36
Policy Brief
