The DOI matches its Crossref record; 77 of the 78 references it cites were found in a registry or an index.
Electric vehicle routing problem: A systematic review and a new comprehensive model with nonlinear energy recharging and consumption
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“When a capsule network (CapsNet) is combined with an improved routing approach (Xiao et al., 2020; Xiao et al., 2021) for classification, it offers greater feature abstraction and representation capabilities without requiring a lot of data or parameters.”
From Deepfake detection using deep learning methods: A systematic and comprehensive review (2024) · cites this paper as Xiao et al., 2021
Citations
Cites
Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints
Solomon, M. M. (1987) · Operations Research · doi:10.1287/opre.35.2.254 · Cited by 4,321
Making Cycling Irresistible: Lessons from The Netherlands, Denmark and Germany
Pucher, J., & Buehler, R. (2008) · Transport Reviews · doi:10.1080/01441640701806612 · Cited by 1,591
The Electric Vehicle-Routing Problem with Time Windows and Recharging Stations
Schneider, M., Stenger, A., & Goeke, D. (2014) · Transportation Science · doi:10.1287/trsc.2013.0490 · Cited by 1,328
Modeling of Load Demand Due to EV Battery Charging in Distribution Systems
Qian, K., Zhou, C., Allan, M., & Yuan, Y. (2011) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2010.2057456 · Cited by 1,268
A Green Vehicle Routing Problem
Erdoğan, S., & Miller-Hooks, E. D. (2011) · Transportation Research Part E Logistics and Transportation Review · doi:10.1016/j.tre.2011.08.001 · Cited by 1,142
Climate change in cities due to global warming and urban effects
McCarthy, M. P., Best, M. J., & Betts, R. A. (2010) · Geophysical Research Letters · doi:10.1029/2010gl042845 · Cited by 821
Power-based electric vehicle energy consumption model: Model development and validation
Fiori, C., Ahn, K., & Rakha, H. A. (2016) · Applied Energy · doi:10.1016/j.apenergy.2016.01.097 · Cited by 641
The electric vehicle routing problem with nonlinear charging function
Montoya, A., Guéret, C., Mendoza, J. E., & Villegas, J. G. (2017) · Transportation Research Part B Methodological · doi:10.1016/j.trb.2017.02.004 · Cited by 639
Routing a mixed fleet of electric and conventional vehicles
Goeke, D., & Schneider, M. (2015) · European Journal of Operational Research · doi:10.1016/j.ejor.2015.01.049 · Cited by 609
Partial recharge strategies for the electric vehicle routing problem with time windows
Keskin, M., & Çatay, B. (2016) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2016.01.013 · Cited by 602
Research works printed but not linked: 2
- Bülent, 2016, A matheuristic approach for solving the electric vehicle routing problem with time windows and fast recharges, Column Gen, 67
- Ángel, 2014, A heuristic approach for the green vehicle routing problem with multiple technologies and partial recharges, Transport Res E Logist Transport Rev, 71, 111, 10.1016/j.tre.2014.09.003 · DOI
Cited by
Sorted by citations
Deepfake detection using deep learning methods: A systematic and comprehensive review
Heidari, A., Jafari Navimipour, N., Dag, H., & Unal, M. (2024) · WIREs Data Mining and Knowledge Discovery · doi:10.1002/widm.1520 · Cited by 349
“When a capsule network (CapsNet) is combined with an improved routing approach (Xiao et al., 2020; Xiao et al., 2021) for classification, it offers greater feature abstraction and representation capabilities without requiring a lot of data or parameters.”
The Optimization of Carbon Emission Prediction in Low Carbon Energy Economy Under Big Data
Luo, J., Zhuo, W., Liu, S., & Xu, B. (2024) · IEEE Access · doi:10.1109/access.2024.3351468 · Cited by 194
Zhang, Y., & Dilanchiev, A. (2022) · Resources Policy · doi:10.1016/j.resourpol.2022.102958 · Cited by 175
Self-citationKhalafian, F., Iliaee, N., Diakina, E., Parsa, P. S., Alhaider, M. M., Masali, M. H., Pirouzi, S., & Zhu, M. (2023) · Journal of Energy Storage · doi:10.1016/j.est.2023.109888 · Cited by 170
State of charge estimation of lithium batteries: Review for equivalent circuit model methods
Tao, Z., Zhao, Z., Wang, C., Huang, L., Jie, H., Li, H., Hao, Q., Zhou, Y., & See, K. Y. (2024) · Measurement · doi:10.1016/j.measurement.2024.115148 · Cited by 157
Metadata
- Authors
- Xiao, Y., Zhang, Y., Kaku, I., Kang, R., & Pan, X.
- Affiliations
- Beihang University (CN)
- Tokyo City University (JP)
- Corresponding author
- Kang, Rui
- Pan, Xing
- Venue
- Renewable and Sustainable Energy Reviews
- Publisher
- Elsevier BV
- Published
- 2021-11
- Volume
- 151
- Pages
- 111567
- ISSN
- 1364-0321 (ISSN-L)
- OpenAlex
- W3195019475
- Cited by
- 236
- References
- 78
- Citations by year
- 2026: 19 · 2025: 42 · 2024: 43 · 2023: 74 · 2022: 54 · 2021: 4
- FWCI
- 4.06
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Renewable and Sustainable Energy Reviews (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Natural Science Foundation of China (71871003, 719710009)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Vehicle Routing Optimization Methods
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
- Physical Sciences › Engineering › Automotive Engineering › Electric and Hybrid Vehicle Technologies
- Keywords
- electric vehicle routing problem, electric vehicles, energy loss, piecewise linear approximation, emission cost, transport logistics, fleet planning
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.
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