The DOI matches its Crossref record; 126 of the 126 references it cites were found in a registry or an index.
Last-mile delivery concepts: a survey from an operational research perspective
Open accessAbstract
In the wake of e-commerce and its successful diffusion in most commercial activities, last-mile distribution causes more and more trouble in urban areas all around the globe. Growing parcel volumes to be delivered toward customer homes increase the number of delivery vans entering the city centers and thus add to congestion, pollution, and negative health impact. Therefore, it is anything but surprising that in recent years many novel delivery concepts on the last mile have been innovated. Among the most prominent are unmanned aerial vehicles (drones) and autonomous delivery robots taking over parcel delivery. This paper surveys established and novel last-mile concepts and puts special emphasis on the decision problems to be solved when setting up and operating each concept. To do so, we systematically record the alternative delivery concepts in a compact notation scheme, discuss the most important decision problems, and survey existing research on operations research methods solving these problems. Furthermore, we elaborate promising future research avenues.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The flying sidekick traveling salesman problem: Optimization of drone-assisted parcel delivery
Murray, C. C., & Chu, A. G. (2015) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2015.03.005 · Cited by 1,715
Vehicle Routing Problems for Drone Delivery
Dorling, K., Heinrichs, J., Messier, G. G., & Magierowski, S. (2017) · IEEE Transactions on Systems, Man, and Cybernetics: Systems · doi:10.1109/tsmc.2016.2582745 · Cited by 1,326
Optimization Approaches for the Traveling Salesman Problem with Drone
Agatz, N., Bouman, P., & Schmidt, M. (2018) · Transportation Science · doi:10.1287/trsc.2017.0791 · Cited by 1,029
Otto, A., Agatz, N., Campbell, J., Golden, B., & Pesch, E. (2018) · Networks · doi:10.1002/net.21818 · Cited by 985
The traveling salesman problem: An overview of exact and approximate algorithms
Laporte, G. (1992) · European Journal of Operational Research · doi:10.1016/0377-2217(92)90138-y · Cited by 971
Facility location models for distribution system design
Klose, A., & Drexl, A. (2005) · European Journal of Operational Research · doi:10.1016/j.ejor.2003.10.031 · Cited by 965
Survey of Green Vehicle Routing Problem: Past and future trends
Lin, C., Choy, K. L., Ho, G. T. S., Chung, S., & Lam, H. Y. (2013) · Expert Systems with Applications · doi:10.1016/j.eswa.2013.07.107 · Cited by 880
A review of recent research on green road freight transportation
Demir, E., Bektaş, T., & Laporte, G. (2014) · European Journal of Operational Research · doi:10.1016/j.ejor.2013.12.033 · Cited by 772
The Role of Surge Pricing on a Service Platform with Self-Scheduling Capacity
Cachon, G. P., Daniels, K. M., & Lobel, R. (2017) · Manufacturing & Service Operations Management · doi:10.1287/msom.2017.0618 · Cited by 724
50th Anniversary Invited Article—City Logistics: Challenges and Opportunities
Savelsbergh, M. W. P., & Woensel, T. V. (2016) · Transportation Science · doi:10.1287/trsc.2016.0675 · Cited by 697
Cited by
Toward a modern last-mile delivery: consequences and obstacles of intelligent technology
Sorooshian, S., Khademi Sharifabad, S., Parsaee, M., & Afshari, A. R. (2022) · Applied System Innovation · doi:10.3390/asi5040082 · Cited by 76
Road logistics decarbonization challenges
Neagoe, M., Hvolby, H.-H., Turner, P., Steger-Jensen, K., & Svensson, C. (2024) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2023.139979 · Cited by 30
Metadata
- Authors
- Boysen, N., Fedtke, S., & Schwerdfeger, S.
- Venue
- OR Spectrum
- Published
- 2020-09-21
- Volume
- 43
- Issue
- 1
- Pages
- 1-58
- ISSN
- 0171-6468 (ISSN-L)
- 1436-6304
- OpenAlex
- W3087935424
- Cited by
- 621
- References
- 126
- FWCI
- 28.77
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Last-mile delivery concepts: a survey from an operational research perspective. https://app.cochat.ai/papers/10.1007/s00291-020-00607-8
- The paper
- Boysen, N., Fedtke, S., & Schwerdfeger, S. (2021). Last-mile delivery concepts: a survey from an operational research perspective. OR Spectrum. https://doi.org/10.1007/s00291-020-00607-8
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.