Genetic algorithm approach for transit route planning and design

The problem of determining an optimal feeder bus route, feeding a major intermodal transfer station (or a central business district), in a service area is considered. Subject to geographic, capacity, and budget constraints, a total cost function, consisting of user and supplier costs, is developed for determining the optimal bus route location and its headway considering intersection delays, irregular grid street patterns, heterogeneous demand distributions, and realistically geographic variations. The criterion for the optimality is to minimize the total cost objective function. The number of feasible bus routes increases drastically with the increased number of the links (streets), and thus this problem is computationally intractable for realistic urban networks. This paper presents examples and demonstrates that the proposed genetic algorithm efficiently converges to the optimal solution, which is validated by the optimal solution obtained by applying an exhaustive search algorithm.