The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.
Analysis of Travel Times and CO 2 Emissions in Time‐Dependent Vehicle Routing
Open accessAbstract
Due to the growing concern over environmental issues, regardless of whether companies are going to voluntarily incorporate green policies in practice, or will be forced to do so in the context of new legislation, change is foreseen in the future of transportation management. Assigning and scheduling vehicles to service a pre‐determined set of clients is a common distribution problem. Accounting for time‐dependent travel times between customers, we present a model that considers travel time, fuel, and CO 2 emissions costs. Specifically, we propose a framework for modeling CO 2 emissions in a time‐dependent vehicle routing context. The model is solved via a tabu search procedure. As the amount of CO 2 emissions is correlated with vehicle speed, our model considers limiting vehicle speed as part of the optimization. The emissions per kilometer as a function of speed are minimized at a unique speed. However, we show that in a time‐dependent environment this speed is sub‐optimal in terms of total emissions. This occurs if vehicles are able to avoid running into congestion periods where they incur high emissions. Clearly, considering this trade‐off in the vehicle routing problem has great practical potential. In the same line, we construct bounds on the total amount of emissions to be saved by making use of the standard VRP solutions. As fuel consumption is correlated with CO 2 emissions, we show that reducing emissions leads to reducing costs. For a number of experimental settings, we show that limiting vehicle speeds is desired from a total cost perspective. This namely stems from the trade‐off between fuel and travel time costs.
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Cites
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Cited by
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 1,312
Bektaş, T., & Laporte, G. (2011) · Transportation Research Part B: Methodological · doi:10.1016/j.trb.2011.02.004 · Cited by 1,219
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
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 607
Energy consumption estimation integrated into the Electric Vehicle Routing Problem
Basso, R., Kulcsár, B., Egardt, B., Lindroth, P., & Sanchez-Diaz, I. (2019) · Transportation Research Part D: Transport and Environment · doi:10.1016/j.trd.2019.01.006 · Cited by 290
Metadata
- Authors
- Jabali, O., VanWoensel, T., & de Kok, A. G.
- Venue
- Production and Operations Management
- Publisher
- SAGE Publications
- Published
- 2012-11
- Volume
- 21
- Issue
- 6
- Pages
- 1060-1074
- ISSN
- 1059-1478 (ISSN-L)
- 1937-5956
- OpenAlex
- W2126043710
- Cited by
- 332
- References
- 25
- FWCI
- 39.36
- Type
- journal article
- Language
- en
- Open access
- green
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- Jabali, O., VanWoensel, T., & de Kok, A. G. (2012). Analysis of Travel Times and CO 2 Emissions in Time‐Dependent Vehicle Routing. Production and Operations Management. https://doi.org/10.1111/j.1937-5956.2012.01338.x
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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.