Scheduling under Uncertainty for Single-Hub Intermodal Freight System

Abstract

This paper examines the optimization of an intermodal system with freight transfers at a single hub by determining when departures should be scheduled on outbound routes, given information about the probabilistic arrivals of vehicles on inbound routes. The intermodal system is modeled with stochastic programming, and the schedule of outbound vehicles is optimized with a genetic algorithm. The model is designed to minimize the expected total cost of operating an intermodal system while considering all capacity constraints arising in the real world. This model allows the system performance to be computed numerically, without the approximations of alternative methods such as simulation. Although the model can be applied to the most general case, the model seems to be especially suitable for analyzing systems with a relatively small number of arrivals on inbound routes. In particular, the model can be successfully applied to situations where statistical or queuing analyses are not applicable because of the small number of events (vehicle arrivals). The authors specifically analyze an intermodal system consisting of multiple inbound truck routes and multiple outbound airline routes. However, the mathematical model developed in this paper is applicable to other combinations of transportation modes.