Flexible-Route Bus Service Design for Urban and Suburban Areas

Abstract

Conventionally, buses serve passengers on fixed routes and with fixed schedules. However, for areas and periods with low trip densities, flexible-route alternatives may be preferable. Flexible-route bus services have great potential, but in order to take advantage of them, efficient management is required, especially in the coordination between conventional and flexible-route buses. In this dissertation, optimization models are developed for coordinating the routes and improving the efficiency of bus transit systems under various circumstances.For given multiple rectangular regions, a method is proposed for integrating, coordinating and optimizing bus services while considering many-to-many travel patterns, demand elasticity, financial constraints, and appropriate service type for various regions. The objective is to maximize welfare, i.e., the sum of producer and consumer surplus. The problem is solved with a hybrid optimization method, where genetic algorithms with bounded integer variables are used to optimize fares, headways, and service zone areas across different zones. These variables, along with service types, are jointly optimized. Sensitivity analyses explore how the choice among conventional and flexible buses depends on the demand, subsidy and demand elasticity parameters. The results also suggest that welfare can increase due to coordination, and these increases tend to be higher in cases with high demand or low subsidy. Additionally, a case study based on real-world data evaluates the model’s scalability, introducing the full GA approach to explore trade-offs between computational efficiency and solution quality. For two connected arbitrarily shaped zones, zone sizes and headways are jointly optimized to achieve minimum average cost per passenger-kilometer. Three types of demand are considered: (1) trips between a service zone and a central business district (CBD); (2) trips between service zones; (3) internal trips within zones. Both coordinated and uncoordinated operation are modeled and then compared in numerical examples. Sensitivity analyses show the need for restricting the minimum zone area if minimum service requirements must be satisfied. A three-step procedure is introduced to determine an appropriate lower bound. For an arbitrarily shaped corridor, a cost minimization model is developed for coordinating fixed-route trunk buses and flexible-route feeder buses. The decision variables include the headways of both services and the zone boundary of each feeder. Leveraging the structure of the problem, the cost function is convex in the headway of the trunk route, enabling a closed-form solution. The headway of each feeder is obtained from a quartic equation with a unique positive real root and the zone boundary is optimized via dynamic programming. The resulting solution is exact and can be computed in polynomial time. A multi-period extension is also proposed to accommodate cyclic variations in demand. Sensitivity analyses show that the optimal number of zones increases when demand increases or when recovery time decreases, while the optimal headways decrease under the same conditions.