Distribution Analysis of Freight Transportation with Gravity Model and Genetic Algorithm

Abstract

The application of a gravity model in freight modeling work on both short-haul and long-haul trips is discussed. A commodity-based gravity model was developed to assess the distribution of freight by long-haul trucks in southeastern Virginia. Although gravity models have been used extensively in transportation studies, little work has been done to address the special characteristics of freight transportation, such as the definition of friction factors and the differences between long-haul and short-haul trips. Results of a recent study of these and similar problems provide valuable insight into freight distribution modeling. A new calibration method that used a genetic algorithm was applied, various commodities were modeled, and the impact of the commodities on the accuracy of the gravity model was studied. Both travel time and travel distance were tested to generate the impedance for friction factors; results showed that for commodity-based long-haul models, travel times were more appropriate for friction factor calculations. In addition, results showed that the gamma function was more suitable than the exponential function for friction factor calculations. Extensive analyses of the causes of variation between observed values and the gravity model outputs are provided. The analyses and conclusions may help modelers better understand characteristics specific to freight transportation and can promote model constructions with greater accuracy and efficiency.