2,674
Views
3
CrossRef citations to date
0
Altmetric
Research Article

Estimation of fuel consumption and selection of the most carbon-efficient route for cold-chain logistics

ORCID Icon, ORCID Icon &
Article: 2075043 | Received 29 Sep 2021, Accepted 30 Apr 2022, Published online: 29 May 2022

References

  • Ali, I., Nagalingam, S., & Gurd, B. (2018). A resilience model for cold chain logistics of perishable products. The International Journal of Logistics Management, 29(3), 922–941. https://doi.org/10.1108/IJLM-06-2017-0147
  • Amorim, P., & Almada-Lobo, B. (2014). The impact of food perishability issues in the vehicle routing problem. Computers & Industrial Engineering, 67, 223–233. https://doi.org/10.1016/j.cie.2013.11.006
  • Baartmans, J. (2015). Refrigerated trailer: electricity or diesel. Bachelor Thesis.
  • Babagolzadeh, M., Shrestha, A., Abbasi, B., Zhang, Y., Woodhead, A., & Zhang, A. (2020). Sustainable cold supply chain management under demand uncertainty and carbon tax regulation. Transportation Research Part D: Transport and Environment, 80, 102245. https://doi.org/10.1016/j.trd.2020.102245
  • Bozorgi, A., Pazour, J., & Nazzal, D. (2014). A new inventory model for cold items that considers costs and emissions. International Journal of Production Economics, 155, 114–125. https://doi.org/10.1016/j.ijpe.2014.01.006
  • Chen, H. K., Hsueh, C. F., & Chang, M. S. (2009). Production scheduling and vehicle routing with time windows for perishable food products. Computers & Operations Research, 36(7), 2311–2319. https://doi.org/10.1016/j.cor.2008.09.010
  • Choi, J., Roberts, D. C., & Lee, E. (2014). Forecast of CO2 emissions from the US transportation sector: Estimation from a double exponential smoothing model. In Journal of the Transportation Research Forum, 53(1424-2016-118052), 63–81. https://doi.org/10.22004/ag.econ.207444
  • CLVEHICLES.COM. (n.d.). A Large Variety Of Brand New Vehicles Ready For You. https://www.clvehicles.com/.
  • Council of Supply Chain Management Professionals. (n.d.). CSCMP supply chain management definitions and glossary. https://cscmp.org/CSCMP/Educate/SCM_Definitions_and_Glossary_of_Terms/CSCMP/Educate/SCM_Definitions_and_Glossary_of_Terms.aspx?hkey=60879588-f65f-4ab5-8c4b-6878815ef921.
  • Demir, E., Bektaş, T., & Laporte, G. (2011). A comparative analysis of several vehicle emission models for road freight transportation. Transportation Research Part D: Transport and Environment, 16(5), 347–357. https://doi.org/10.1016/j.trd.2011.01.011
  • Demir, E., Bektaş, T., & Laporte, G. (2014). A review of recent research on green road freight transportation. European Journal of Operational Research, 237(3), 775–793. https://doi.org/10.1016/j.ejor.2013.12.033
  • Dong, Y., Xu, M., & Miller, S. A. (2021). Overview of cold chain development in China and methods of studying its environmental impacts. Environmental Research Communications, 2(12), 122002. https://doi.org/10.1088/2515-7620/abd622
  • DRX AUTO. (n.d). Refrigerated truck. https://www.customsvehicle.com/Refrigerated-truck-pl8819685.html.
  • Eder, L., Filimonova, I., Nemov, V., Komarova, A., & Sablin, K. (2019). Ecological aspects of economical development: Issues of forecast greenhouse gas emissions in road transport in Europe and regions of Russia. In E3S Web of Conferences (Vol. 80, p. 03010). EDP Sciences.
  • Gharehyakheh, A., Krejci, C. C., Cantu, J., & Rogers, K. J. (2020). A multi-objective model for Sustainable perishable food distribution considering the impact of temperature on vehicle emissions and product shelf life. Sustainability, 12(16), 6668. https://doi.org/10.3390/su12166668
  • Kazancoglu, Y., Ozbiltekin-Pala, M., & Ozkan-Ozen, Y. D. (2021). Prediction and evaluation of greenhouse gas emissions for sustainable road transport within Europe. Sustainable Cities and Society, 70, 102924. https://doi.org/10.1016/j.scs.2021.102924
  • Kouridis, C., Gkatzoflias, D., Kioutsioukis, I., Ntziachristos, L., Pastorello, C., & Dilara, P. (2010). Uncertainty estimates and guidance for road transport emission calculations. Publications Office of the European Union, EUR, 24296.
  • Lan, H., He, Q. F., Bian, Z., & Jin, Z. H. (2015). Distribution routing optimization of cold chain logistics with consideration of road traffic conditions. Journal of Dalian Maritime University, 11(41), 67–74.
  • Lee, J., Choi, J. S., Hu, H., & Yoon, T. (2019). A method for the estimation of greenhouse gas emissions based on road geometric design and its application to South Korea. International Journal of Sustainable Transportation, 13(1), 65–80. https://doi.org/10.1080/15568318.2018.1437487
  • Leng, L., Zhang, C., Zhao, Y., Wang, W., Zhang, J., & Li, G. (2020a). Biobjective Low-carbon location-routing problem for cold chain logistics: Formulation and heuristic approaches. Journal of Cleaner Production, 122801. https://doi.org/10.1016/j.jclepro.2020.122801
  • Leng, L., Zhang, J., Zhang, C., Zhao, Y., Wang, W., & Li, G. (2020b). Decomposition-based hyperheuristic approaches for the Bi-objective cold chain considering environmental effects. Computers & Operations Research, 105043. https://doi.org/10.1016/j.cor.2020.105043
  • Leng, L., Zhang, J., Zhang, C., Zhao, Y., Wang, W., & Li, G. (2020c). A novel bi-objective model of cold chain logistics considering location-routing decision and environmental effects. PloS One, 15(4), e0230867. https://doi.org/10.1371/journal.pone.0230867
  • Leng, L., Zhao, Y., Wang, Z., Zhang, J., Wang, W., & Zhang, C. (2019a). A novel hyper-heuristic for the biobjective regional low-carbon location-routing problem with multiple constraints. Sustainability, 11(6), 1596. https://doi.org/10.3390/su11061596
  • Leng, L., Zhao, Y., Zhang, J., & Zhang, C. (2019b). An effective approach for the multiobjective regional low-carbon location-routing problem. International Journal of Environmental Research and Public Health, 16(11), 2064. https://doi.org/10.3390/ijerph16112064
  • Li, L., Yang, Y., & Qin, G. (2019). Optimization of integrated inventory routing problem for cold chain logistics considering carbon footprint and carbon regulations. Sustainability, 11(17), 4628. https://doi.org/10.3390/su11174628
  • Lin, D., Zhang, Z., Wang, J., Yang, L., Shi, Y., & Soar, J. (2019). Optimizing urban distribution routes for perishable foods considering carbon emission reduction. Sustainability, 11(16), 4387. https://doi.org/10.3390/su11164387
  • Mahtab, Z., Azeem, A., Ali, S. M., Paul, S. K., & Fathollahi-Fard, A. M. (2021). Multi-objective robust-stochastic optimisation of relief goods distribution under uncertainty: A real-life case study. International Journal of Systems Science: Operations & Logistics, 1–22. https://doi.org/10.1080/23302674.2021.1879305
  • Matthews, H. D., Gillett, N. P., Stott, P. A., & Zickfeld, K. (2009). The proportionality of global warming to cumulative carbon emissions. Nature, 459(7248), 829–832. https://doi.org/10.1038/nature08047
  • Musavi, M., & Bozorgi-Amiri, A. (2017). A multi-objective sustainable hub location-scheduling problem for perishable food supply chain. Computers & Industrial Engineering, 113, 766–778. https://doi.org/10.1016/j.cie.2017.07.039
  • Paul, S., Kabir, G., Ali, S. M., & Zhang, G. (2020). Examining transportation disruption risk in supply chains: A case study from Bangladeshi pharmaceutical industry. Research in Transportation Business & Management, 37, 100485. https://doi.org/10.1016/j.rtbm.2020.100485
  • Qin, G., Tao, F., & Li, L. (2019). A vehicle routing optimization problem for cold chain logistics considering customer satisfaction and carbon emissions. International Journal of Environmental Research and Public Health, 16(4), 576. https://doi.org/10.3390/ijerph16040576
  • Roy, S., Das, M., Ali, S. M., Raihan, A. S., Paul, S. K., & Kabir, G. (2020). Evaluating strategies for environmental sustainability in a supply chain of an emerging economy. Journal of Cleaner Production, 262, 121389. https://doi.org/10.1016/j.jclepro.2020.121389
  • Shukla, M., & Jharkharia, S. (2013). Agri-fresh produce supply chain management: A state-of-the-art literature review. International Journal of Operations & Production Management, 33(2), 114–158. https://doi.org/10.1108/01443571311295608
  • Solomon, S., Plattner, G. K., Knutti, R., & Friedlingstein, P. (2009). Irreversible climate change due to carbon dioxide emissions. Proceedings of the National Academy of Sciences, 106(6), 1704–1709. https://doi.org/10.1073/pnas.0812721106
  • Stott, P. A., & Kettleborough, J. A. (2002). Origins and estimates of uncertainty in predictions of twenty-first century temperature rise. Nature, 416(6882), 723–726. https://doi.org/10.1038/416723a
  • Tassou, S. A., De-Lille, G., & Lewis, J. (2012). Food transport refrigeration. Centre for Energy and Built Environment Research, Brunel University, UK.
  • Tirumalachetty, S., Kockelman, K. M., & Nichols, B. G. (2013). Forecasting greenhouse gas emissions from urban regions: Microsimulation of land use and transport patterns in Austin, Texas. Journal of Transport Geography, 33, 220–229. https://doi.org/10.1016/j.jtrangeo.2013.08.002
  • Ubeda, S., Arcelus, F. J., & Faulin, J. (2011). Green logistics at Eroski: A case study. International Journal of Production Economics, 131(1), 44–51. https://doi.org/10.1016/j.ijpe.2010.04.041
  • Wang, S., Tao, F., & Shi, Y. (2018). Optimization of location–routing problem for cold chain logistics considering carbon footprint. International Journal of Environmental Research and Public Health, 15(1), 86. https://doi.org/10.3390/ijerph15010086
  • Wang, Y., Zhang, J., Guan, X., Xu, M., Wang, Z., & Wang, H. (2020b). Collaborative multiple centers fresh logistics distribution network optimization with resource sharing and temperature control constraints. Expert Systems with Applications, 165, 113838. https://doi.org/10.1016/j.eswa.2020.113838
  • Wang, Z., Leng, L., Wang, S., Li, G., & Zhao, Y. (2020a). A hyperheuristic approach for location-routing problem of cold chain logistics considering fuel consumption. Computational Intelligence and Neuroscience, 2020, 8395754. https://doi.org/10.1155/2020/8395754
  • Weisbrod, R. (2011). The Geography of transport systems. Journal of Urban Technology, 18(2), 99–104. https://doi.org/10.1080/10630732.2011.603579
  • Wong, E. Y. C., Chan, F. F. Y., & So, S. (2020). Consumer perceptions on product carbon footprints and carbon labels of beverage merchandise in Hong Kong. Journal of Cleaner Production, 242, 118404. https://doi.org/10.1016/j.jclepro.2019.118404
  • Wong, E. Y. C., Tai, A. H., & Zhou, E. (2018). Optimising truckload operations in third-party logistics: A carbon footprint perspective in volatile supply chain. Transportation Research Part D: Transport and Environment, 63, 649–661. https://doi.org/10.1016/j.trd.2018.06.009
  • World Bank. (n.d.). Agriculture, forestry, and fishing, value added (% of GDP). http://data.worldbank.org/indicator/NV.AGR.TOTL.ZS/countries.
  • Xiao, X., Zhu, Z., Fu, Z., Mu, W., & Zhang, X. (2018). Carbon footprint constrained profit maximization of table grapes cold chain. Agronomy, 8(7), 125. https://doi.org/10.3390/agronomy8070125
  • Xiao, Y., Zhao, Q., Kaku, I., & Xu, Y. (2012). Development of a fuel consumption optimization model for the capacitated vehicle routing problem. Computers & Operations Research, 39(7), 1419–1431. https://doi.org/10.1016/j.cor.2011.08.013
  • Zhang, L. Y., Tseng, M. L., Wang, C. H., Xiao, C., & Fei, T. (2019). Low-carbon cold chain logistics using ribonucleic acid-ant colony optimization algorithm. Journal of Cleaner Production, 233, 169–180. https://doi.org/10.1016/j.jclepro.2019.05.306
  • Zhao, B., Gui, H., Li, H., & Xue, J. (2020). Cold chain logistics path optimization via improved multi-objective ant colony algorithm. IEEE Access, 8, 142977–142995. https://doi.org/10.1109/ACCESS.2020.3013951
  • Zhao, Y., Leng, L. L., Wang, S., & Zhang, C. (2018). Evolutionary hyper-heuristics for low-carbon location-routing problem with heterogeneous fleet. Control Decis, 35(2), 257–271. https://doi.org/10.13195/j.kzyjc.2018.0756 (in Chinese).

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.