R. Kutadinata, R. Thompson, and S. Winter, “Cost-efficient Co-modal Ride-sharing Scheme Through Anticipatory Dynamic Optimisation,” in Proceedings of the 23rd ITS World Congress, 2016.
This paper considers the vehicle routing problem when dealing with a co-modal demand-responsive transport service. The vehicles in the service are shared among two modes of customers, passengers and goods deliveries. In particular, this paper develops a conceptual model in order to explore the performance of such a service with two different optimisation algorithms, namely deterministic re-optimisation and the Multiple Scenario Approach (MSA). An important contribution of this work is the formulation of the co-modality as a pick-up and delivery problem with time windows (PDPTW). In addition, the effect of using various constraints and penalty functions in the optimisation formulation will be investigated. The experiment will be carried out in a vehicle routing simulation developed in MATLAB by using a demand scenario obtained from the Victorian Integrated Survey of Travel and Activity (VISTA) data. In the model, the performance of the algorithms is measured by the operating cost, the number of customers whose time-window constraints are violated, and the average wait and detour time.
Lee, A., M. Savelsbergh (2014), An extended demand responsive connector. EURO Journal on Transportation and Logistics, http://dx.doi.org/10.1007/s13676-014-0060-6.
The need for viable public transit systems has been well documented and so has the role that so-called flexible transport systems can play. Flexible transport services offer great potential for increases in mobility and convenience and decreases in travel times and operating costs. One such service is the demand responsive connector, which transports commuters from residential addresses to transit hubs via a shuttle service, from where they continue their journey via a traditional timetabled service. To access this service, commuter and service provider agree on an earliest time the commuter must be available for collection and a latest time the commuter will arrive at a transit station. We investigate various options for implementing a demand responsive connector and the associated vehicle-scheduling problems. Previous work has only considered regional systems, where vehicles drop passengers off at a predetermined station; one of our contributions is to relax that restriction and investigate the benefits of allowing alternative transit stations. An extensive computational study shows that the more flexible system offers cost advantages over regional systems, especially when transit services are frequent, or transit hubs are close together, with little impact on passenger convenience.