Abstract
A critical link in the overnight Express Package services is the on-time arrival of trucks at local airport terminals. Truck delays can delay the package sorting process, which can in turn delay aircraft departures from the local terminal, as well as aircraft departures from hub terminals that depend on timely aircraft arrivals. In this paper, the design of a real-time logistics information system (RLIS) for trucking industry was addressed, considering the effects of traffic congestion during rush hour. Two types of forecasting methods, time series models and nonlinear fuzzy reasoning, were created and embedded into the RLIS. The results from practical web services reveal a substantial improvement of the truck scheduling performance and help decision makers determine schedule coordination between ground transportation and aircraft departures at airport cargo terminals.
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