OPTIMIZING SKIP STOP SERVICE IN PASSENGER RAIL TRANSPORTATION

Two-track passenger rail lines typically operate with all trains serving every station. Without additional infrastructure, transit planners have limited options to improve travel times. Service could be improved by operating a skip-stop service where trains only serve a subset of all the station stops. A skip-stop pattern must find an optimal balance between faster passenger travel times and lower service frequencies at each station. A mixed integer formulation is proposed to analyze this tradeoff; however, the mixed integer formulation could not scale efficiently to analyze a large scale commuter line. A genetic algorithm is presented to search the solution space incorporating a larger problem scope and complexity. In a case study of a Midwest commuter line, overall passenger travel time could be decreased by 9.5%. Both analyses can give insights to transit operators on how to improve their service to their customers and increase ridership.