Coordinated Optimization of Community Shuttle Timetable Joint for Metros Based on Genetic Algorithm

Community shuttle plays an important role in public transit microcirculation, and developing an optimal timetable for the community shuttle to make it dovetail with the metro schedule well is an important job. The paper presents a solution for coordinated timetable designing problem with the objective of minimizing the total cost, including user cost and shuttle supplier cost. User cost can be divided into four parts further: user access cost, in-vehicle cost, wait cost and transfer cost, where wait cost and supplier cost are related to the shuttle headway directly, and transfer cost is related to the timetable generated by the headway. So in the process of solving the problem, a heuristic algorithm is developed to determine the minimized transfer cost for a given headway, then a genetic algorithm is used to determine the optimal headway. At last, a case study based on passenger count data of an existing route served for Tian Tongyuan Community in Beijing is presented. The result shows that the optimal timetable obtained from the model saves much cost compared with the existing timetable.