LAUSR

The feeder bus, as an important component of urban public transportation systems, is capable of filling the existing service gap left by urban rail transit to satisfy feeder demand. Two challenges to taking advantage of the feeder bus are identified. The first challenge is to identify the service gap, and the second one is to strengthen the coordination of multilevel urban traffic modes. Given these two challenges, this paper established a route design model that introduced a feeder bus demand coefficient to quantify feeder demand for each bus stop. To assist the design of feeder bus routes, an optimization approach based on the tabu search algorithm was proposed. Considering the sizeable combinational optimization problem, the algorithm decomposed this problem into three phases: feeder area partition, candidate stop selection, and route design problem. In the first phase, the entire area was partitioned into several subareas and the specific boundary nodes were moved into an adjacent subarea. Then, the stops with the minimum overall travel cost from every subarea were chosen as candidate ones under the limit of operating costs. The last step was to find the shortest circular route to visit each candidate stop and determine the operating direction. The proposed optimization had been implemented in a downtown area of Suzhou, China, in order to verify its effectiveness through the performance in terms of the quality of optimal solutions and computing efficiency. In addition, a possibility of simplifying a multiple circular route design problem to a single route design problem utilizing spatial clustering is provided to enhance the computing efficiency in a large-scale network.