By Hiral Nisar and Joshua Rosenzweig, MIT SCM Class of 2014
In the freight transportation industry, economies of scale can be achieved by aggregating similar loads in geographic areas that are in close proximity to each other. However, since companies don’t know future demand, it can be difficult to gauge whether or not loads should be accepted, particularly where unfamiliar geographies are involved.
For this project, the researchers wanted to create and validate a model to determine if historical demand data can be used by retail firms operating private fleets to make effective order acceptance/rejection decisions in real time. The model would help companies eliminate unprofitable orders in a short-haul transportation environment. They developed a Java tool that decides in an instant whether or not to accept loads depending on the order location and time of receipt.