Compatibility-Based Approach for Routing and Scheduling the Demand Responsive Connector

Abstract

This study concentrates on the routing and scheduling problem of Demand Responsive Connector to build feeder plans for people traveling from and to transit hub. An in-depth analysis on the characteristics of feeder services was implemented to inspire the compatibility-based algorithm design. With the goal of reducing operating cost and passenger inconvenience, the proposed algorithm took several factors critical to the real-word operation into consideration, such as double time window assurance (the time constraints at the beginning and end of passenger travels), the flexibility of feeder plans, and the number of vehicles. Our method was validated on numerical instances of 400, 600, 800 and 1000 passengers. Simulation results show that the compatibility-based algorithm can effectively reduce the number of vehicles with acceptable increase of passengers' inconvenience, and can improve the algorithm efficiency considerably. In addition, the setting of flexible time window of shutter plan can hold some elasticity for feeder services. Sensitivity analysis was conducted to help service providers evaluate the trade-off between the operation cost and level of service. INDEX TERMS Compatibility-based approach, demand responsive connector, routing and scheduling.

Integrating Passenger Incentives to Optimize Routing for Demand-Responsive Customized Bus Systems

“…The DRT is a route-variable public transportation mode that serves flexible trips without a fixed transit route based on users' requests. Existing studies indicate that DRT is helpful for emission reduction and improvement for public mobility [10,11], Reference [3] thoroughly summarized the taxonomy of DRT, including (1) the dial-a-ride service, which dynamically dispatches vehicles in response to users' trip requests, (2) the shuttle bus which deals with trips of oneto-many and many-to-one locations like airport shuttles [12], (3) Jitney which serves fewer people using mini-bus, and (4) customized bus which collects trip requests and plans routes according to collected trips.…”

Optimizing Centralized Dispatching of Flexible Feeder Transit considering Transfer Coordination with Regular Public Transit

“…Some studies have proposed machine learning [27], hybrid evolutionary [28], and Tabu search [29,30] methods for the dial-a-ride problem; GA [12,31] and heuristic algorithm [11,24] are among the most successful approximate approaches for solving the dial-a-ride problem. GA was tested on a set of medium-scale problem scenarios, and it was found to be accessible and efficient.…”

“…Lee et al [23] relaxed the restriction of alighting stations and allowed vehicles to drop passengers off at an alternative transit station. Lu et al [24] considered doubletime window assurance and group travel. Alonso-Mora et al [25] focused on dynamic high-capacity carpooling and designed many-to-one, flexible bus demand response strategies based on the vehicle-demand analysis.…”

“…Based on this assumption, many studies [6][7][8][9][10]23] have attempted to minimize the operation costs in terms of operation time and distance, and one study [9] attempted to minimize the total passenger ride time. In addition, some studies [24,26] considered the objectives of the operating costs and passengers in terms of travel time and disutility of delay. However, in practice, it is not economical to provide service to all passengers because of the spatiotemporal dispersion of passenger travel.…”

Heuristic approach for the multiobjective optimization of the customized bus scheduling problem

“…In transportation, CB is not a novel public-transport-service concept, but a variant of the DRT service. Early DRT studies presented various DRT systems that provide flexible transport services (FTS), including the topic of service performance [1][2][3][4], vehicle routing model [5][6][7][8][9][10], geometric features in the service area [11], critical demand density [12] and feet scheduling and dispatching issues [13][14][15][16][17][18][19][20]. Thereafter, the concept of DRT as a niche market has been broadened to include a wider range of flexible, DRT services and is increasingly referred to as FTS [21][22][23][24][25][26].…”