This PhD so far has focussed on two distinct optimisation problems pertaining to public transport, as detailed below:
Within public transit systems, so-called flexible transport systems have great potential to of- fer 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 ad- dresses to transit hubs via a shuttle service, from where they continue their journey via a traditional timetabled service. 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 -- we relax that condition 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, without little impact on customer convenience.
A compliment to public transport systems is that of ad hoc ride sharing, where participants (either offering or requesting rides) are paired with participants wanting the reverse, by some central service provider. Although such schemes are currently in operation, the lack of certainty offered to riders (i.e. the risk of not finding a match, or a driver not turning up) discourages potential users. Critically, this can prevent the system from reaching a "critical mass" and becoming self sustaining. We are investigating the situation where the provider has access to a fleet of dedicated drivers, and may use these to service riders, especially when such a system is in its infancy. We investigate some of the critical pricing issues surrounding this problem, present some optimisation models and provide some computational results.