Integration of Passenger and Freight Rail Scheduling: Final Report METRANS Project 15-04

0163007910418391542017Final Report 08/15/2015-08/14/2016PDFTech ReportCA16-2935METRANS Project 15-0465A0533Task Order 010Freight and passenger trafficFreight trainsSchedulingRailroad transportationPassenger trainsTrackage rightsTravel timeAlgorithmsFreight transportationRoutingSimulationTraffic delayTrainRailMETRANSUSCResearchModelingTrainsPlanningToolPassengerFreightFreight TransportationOperations and Traffic ManagementPlanning and ForecastingRailroadsCaliforniaUnited StatesCalifornia. Department of TransportationLiu, LiangCarvajal, SantiagoFu, LunceMETRANS Transportation Center (Calif.)University of Southern California. Dept. of Industrial and Systems EngineeringCalifornia. Department of TransportationUniversity Transportation Centers Program (U.S.)United States. Dept. of TransportationUS Transportation CollectionIn the United States, freight railways are one of the major ways to transport goods from ports to inland destinations. According to an Association of American Railroad\u2019s study, rail companies move more than 40% of the nation\u2019s total freight. Given the fact that the freight railway industry is already running without much excess capacity, better planning and scheduling tools are needed to effectively manage the scarce resources, to cope with the rapidly increasing demand for railway transportation. The integration of freight train and passenger train scheduling and dispatching is an important railroad management task. Leveraging the current railroad trackage to meet the expanding demand in the future is a challenge. The objective of this project was to improve the efficiency of freight trains by reducing their traveling times while maintaining the punctuality of passenger trains. Thus, we proposed a decomposition based heuristic that first minimizes the tardiness of passenger trains and second minimizes the travel times of the freight trains. Our proposed algorithm solves the routing and scheduling problem for real world size rail networks efficiently. We performed simulation experiments on an actual rail network in Southern California to test our proposed heuristic approach. The proposed solution reduces the average travel time of freight trains and reduces the average tardiness of passenger trains over other existing approaches