Publication Type
Journal Article
Version
publishedVersion
Publication Date
1-2022
Abstract
This research introduces a new variant of the two-echelon vehicle routing problem (2EVRP) called the two-echelon vehicle routing problem with transshipment nodes and occasional drivers (2EVRP-TN-OD). In addition to city freighters in the second-echelon network, a set of occasional drivers (ODs) is available to serve customers. ODs are the basis of a crowd-shipping system in which crowds with planned trips are willing to take detours to deliver packages in exchange for some compensation. To serve customers, ODs collect the assigned packages at either satellite served by first-echelon trucks or transshipment nodes served by city freighters. We formulate this problem as a mixed-integer nonlinear programming model and develop an adaptive large neighborhood search (ALNS) to solve it. New problem-specific destroy and repair operators and a tailored local search procedure are embedded into ALNS to deal with the problem’s unique characteristics. The experiments show that the proposed ALNS effectively solves 2EVRP-TN-OD by outperforming Gurobi in terms of both solution quality and computational time. Moreover, the experiments confirm that employing occasional drivers leads to lower operational costs. Sensitivity analyses on the characteristics of occasional drivers and the impact of transshipment nodes are presented as interesting managerial insights from 2EVRP-TN-OD.
Discipline
Numerical Analysis and Scientific Computing | Operations Research, Systems Engineering and Industrial Engineering | Transportation
Research Areas
Data Science and Engineering
Publication
Journal of Advances Transportation
Volume
2022
Issue
1
First Page
1
Last Page
23
ISSN
0197-6729
Identifier
10.1155/2022/5603956
Publisher
Wiley
Embargo Period
2-12-2025
Citation
YU, Vincent F.; NGUYEN, Minh P. K.; PUTRA, Kuza; GUNAWAN, Aldy; and DHARMA, I. Gusti Bagus Budi.
The Two-echelon vehicle routing problem with transshipment nodes and occasional drivers: Formulation and adaptive large neighborhood search heuristic. (2022). Journal of Advances Transportation. 2022, (1), 1-23.
Available at: https://ink.library.smu.edu.sg/sis_research/10100
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Additional URL
https://doi.org/10.1155/2022/5603956
Included in
Numerical Analysis and Scientific Computing Commons, Operations Research, Systems Engineering and Industrial Engineering Commons, Transportation Commons
