Hai Wang (2017) Routing and Scheduling for a Last-Mile Transportation System. Transportation Science 53(1):131-147.
The last–mile problem concerns the provision of travel services from the nearest public transportation node to a passenger’s home or other destination. We study the operation of an emerging last–mile transportation system (LMTS) with batch demands that result from the arrival of groups of passengers who desire last–mile service at urban metro stations or bus stops. Routes and schedules are determined for a multivehicle fleet of delivery vehicles, with the objective of minimizing passenger waiting time and riding time. An exact mixed-integer programming (MIP) model for LMTS operations is presented first, which is difficult to solve optimally within acceptable computational times. Computationally feasible heuristic approaches are then developed: a myopic operating strategy that uses only demand information from trains that have already arrived, a metaheuristic approach based on a tabu search that employs demand information over the entire service horizon, and a two-stage method that solves the MIP model approximately over the entire service horizon. These approaches are implemented in a number of computational experiments to evaluate the system’s performance, and demonstrate that LMTS is notably preferable to a conventional service system under certain conditions.