Publication Type
Journal Article
Version
acceptedVersion
Publication Date
1-2019
Abstract
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.
Keywords
Last mile, batch demand, routing and scheduling, mixed integer programming, myopic strategy, tabu search
Discipline
Operations Research, Systems Engineering and Industrial Engineering | Transportation
Research Areas
Intelligent Systems and Optimization
Publication
Transportation Science
Volume
53
Issue
1
First Page
131
Last Page
147
ISSN
0041-1655
Identifier
10.1287/trsc.2017.0753
Publisher
INFORMS (Institute for Operations Research and Management Sciences)
Citation
WANG, Hai.
Routing and scheduling for a last-mile transportation system. (2019). Transportation Science. 53, (1), 131-147.
Available at: https://ink.library.smu.edu.sg/sis_research/3689
Copyright Owner and License
Author
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1287/trsc.2017.0753
Included in
Operations Research, Systems Engineering and Industrial Engineering Commons, Transportation Commons