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An optimal control theory approach for freight structure path evolution post-COVID-19 pandemic

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  • Lu, Changxiang
  • Ye, Yong
  • Fang, Yongjun
  • Fang, Jiaqi

Abstract

After the outbreak of COVID-19, the freight demand fell briefly, and as production resumed, the trucking share rate increased again, further increasing energy consumption and environmental pollution. To optimize the sudden changing freight structure, the study aims on developing an evolution model based on Markov's theory to estimate the freight structure post-COVID-19. The current study applies economic cybernetics to establish a freight structural adjustment path optimization model and solve the problem of how much freight transportation should increase each year under the premise that the total turnover of the freight industry continues to grow, and how many years it will take at least to reach a reasonable freight structure. The freight transport structure of China is used to examine the feasibility of the proposed model. The finding indicates that the development of China's freight transport structure is at an adjustment period and should enter a stable period by 2035 and the COVID-19 makes it harder to adjust the freight structure. Increasing the growth rate of the freight volume of railway and waterway transportation is the key to realizing the optimization of the freight structure, and the freight structure path optimization method can realize the rationalization of the freight structure in advance.

Suggested Citation

  • Lu, Changxiang & Ye, Yong & Fang, Yongjun & Fang, Jiaqi, 2023. "An optimal control theory approach for freight structure path evolution post-COVID-19 pandemic," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
  • Handle: RePEc:eee:soceps:v:85:y:2023:i:c:s0038012122002312
    DOI: 10.1016/j.seps.2022.101430
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    References listed on IDEAS

    as
    1. Daniel Kaszubowski, 2019. "A Method for the Evaluation of Urban Freight Transport Models as a Tool for Improving the Delivery of Sustainable Urban Transport Policy," Sustainability, MDPI, vol. 11(6), pages 1-23, March.
    2. Seungjin Shin & Hong-Seung Roh & Sung Ho Hur, 2019. "Characteristics Analysis of Freight Mode Choice Model According to the Introduction of a New Freight Transport System," Sustainability, MDPI, vol. 11(4), pages 1-13, February.
    3. Shiqing Zhang & Jianwei Wang & Wenlong Zheng, 2018. "Decomposition Analysis of Energy-Related CO 2 Emissions and Decoupling Status in China’s Logistics Industry," Sustainability, MDPI, vol. 10(5), pages 1-21, April.
    4. Rich, J. & Kveiborg, O. & Hansen, C.O., 2011. "On structural inelasticity of modal substitution in freight transport," Journal of Transport Geography, Elsevier, vol. 19(1), pages 134-146.
    5. Bhattarai, Santosh & Golias, Mihalis M. & Mishra, Sabyasachee & Talebian, Ahmadreza, 2020. "Multidimensional resource allocation for freight transportation project planning and decision making," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 95-110.
    6. Keya, Nowreen & Anowar, Sabreena & Eluru, Naveen, 2019. "Joint model of freight mode choice and shipment size: A copula-based random regret minimization framework," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 97-115.
    7. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, January.
    8. Jiaqi Fang & Hanping Hou & Changxiang Lu & Haiyun Pang & Qingshan Deng & Yong Ye & Lingle Pan, 2021. "A new scheduling method based on sequential time windows developed to distribute first-aid medicine for emergency logistics following an earthquake," PLOS ONE, Public Library of Science, vol. 16(2), pages 1-18, February.
    9. Lee, Hsiu-Yun & Chen, Show-Lin, 2006. "Why use Markov-switching models in exchange rate prediction?," Economic Modelling, Elsevier, vol. 23(4), pages 662-668, July.
    10. Fredrik Bärthel & Johan Woxenius, 2004. "Developing intermodal transport for small flows over short distances," Transportation Planning and Technology, Taylor & Francis Journals, vol. 27(5), pages 403-424, October.
    11. Rich, J. & Holmblad, P.M. & Hansen, C.O., 2009. "A weighted logit freight mode-choice model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(6), pages 1006-1019, November.
    12. Shinghal, Nalin & Fowkes, Tony, 2002. "Freight mode choice and adaptive stated preferences," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 38(5), pages 367-378, September.
    13. Wang, Zhihong & Li, Yangyang & Gu, Fu & Guo, Jianfeng & Wu, Xiaojun, 2020. "Two-sided matching and strategic selection on freight resource sharing platforms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
    14. Takahashi, Katsuhiko & Morikawa, Katsumi & Myreshka & Takeda, Daisuke & Mizuno, Akihiko, 2007. "Inventory control for a MARKOVIAN remanufacturing system with stochastic decomposition process," International Journal of Production Economics, Elsevier, vol. 108(1-2), pages 416-425, July.
    15. Serva, M. & Fulco, U.L. & Gléria, I.M. & Lyra, M.L. & Petroni, F. & Viswanathan, G.M., 2006. "A Markov model of financial returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 363(2), pages 393-403.
    16. Fariba Goodarzian & Peiman Ghasemi & Angappa Gunasekaren & Ata Allah Taleizadeh & Ajith Abraham, 2022. "A sustainable-resilience healthcare network for handling COVID-19 pandemic," Annals of Operations Research, Springer, vol. 312(2), pages 761-825, May.
    17. Li, Wei & Sun, Wen & Li, Guomin & Cui, Pengfei & Wu, Wen & Jin, Baihui, 2017. "Temporal and spatial heterogeneity of carbon intensity in China's construction industry," Resources, Conservation & Recycling, Elsevier, vol. 126(C), pages 162-173.
    18. Silos, Pedro, 2006. "Assessing Markov chain approximations: A minimal econometric approach," Journal of Economic Dynamics and Control, Elsevier, vol. 30(6), pages 1063-1079, June.
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