Optimal Routing Design of a Community Shuttle for Metro Stations

Abstract

The optimization of a community shuttle route plays an important role in the efficient operation of public transit microcirculation. This paper develops a solution for the optimal routing design problem with the objective of minimizing the total cost, including user and supplier costs, considering passenger traffic demand and budget constraints. The optimization variables include route and headway. To calculate the user cost, a heuristic algorithm for locating stops is presented. Then the optimized headway corresponding to a given bus route is confirmed by minimizing the total cost function. In solving the problem, a depth-first search algorithm (DFS) and a genetic algorithm (GA) are both presented. By comparing the results and the CPU time of the two algorithms, this paper demonstrated that GA is reliable and more efficient than DFS. The impacts of route length and the maximum tolerable walking distance on the cost and headway are also analyzed.