IDEAS home Printed from https://ideas.repec.org/a/spr/endesu/v23y2021i9d10.1007_s10668-021-01236-z.html
   My bibliography  Save this article

Robust optimization approach to two-echelon agricultural cold chain logistics considering carbon emission and stochastic demand

Author

Listed:
  • Ying Ji

    (University of Shanghai for Science and Technology)

  • Jianhui Du

    (University of Shanghai for Science and Technology)

  • Xiaoqing Wu

    (Guangzhou University)

  • Zhong Wu

    (University of Shanghai for Science and Technology)

  • Deqiang Qu

    (University of Shanghai for Science and Technology)

  • Dan Yang

    (Cranfield University)

Abstract

Cold chain logistics has become one of the main sources of carbon emissions. Meanwhile, the implementation of low-carbon economy has become an inevitable way to promote sustainable development. However, previous studies on the cold chain inventory routing problem (IRP) paid less attention to the cost of carbon emissions. In this paper, a linear programming (LP) model is established, which takes the costs of vehicle transportation, time window and carbon emission into consideration. Although the simple LP model is easy to be solved, it cannot handle the problems with uncertainty. Therefore, in order to overcome the influence of uncertainty, the proposed LP model is developed into three low-carbon robust optimization (RO) models. In addition, this paper takes a cold chain logistics enterprise in Yangtze River Delta as an example for empirical analysis. The results of the case study prove that the RO models can quickly solve the problems with uncertainty and still maintain robustness, while the LP model has failed. Specifically, the R-ellipsoid model produces the best result among the three RO models. It is suggested that when the carbon emission tax increases, the decision makers tend to choose a better path planning scheme, which will not only reduce the total cost, but also obtain environmental benefits. Finally, the findings of this paper generate some implications for the low-carbon transformation of cold chain logistics enterprises.

Suggested Citation

  • Ying Ji & Jianhui Du & Xiaoqing Wu & Zhong Wu & Deqiang Qu & Dan Yang, 2021. "Robust optimization approach to two-echelon agricultural cold chain logistics considering carbon emission and stochastic demand," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(9), pages 13731-13754, September.
    • Handle: RePEc:spr:endesu:v:23:y:2021:i:9:d:10.1007_s10668-021-01236-z
    DOI: 10.1007/s10668-021-01236-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10668-021-01236-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10668-021-01236-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Chen, Wenbo, 2018. "Retailer-driven carbon emission abatement with consumer environmental awareness and carbon tax: Revenue-sharing versus Cost-sharingAuthor-Name: Yang, Huixiao," Omega, Elsevier, vol. 78(C), pages 179-191.
    2. Zhang, Yue-Jun & Da, Ya-Bin, 2015. "The decomposition of energy-related carbon emission and its decoupling with economic growth in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 1255-1266.
    3. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    4. S I Harewood, 2002. "Emergency ambulance deployment in Barbados: a multi-objective approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(2), pages 185-192, February.
    5. Zhang, Jiekuan & Zhang, Yan, 2018. "Carbon tax, tourism CO2 emissions and economic welfare," Annals of Tourism Research, Elsevier, vol. 69(C), pages 18-30.
    6. Lin, Qi & Zhao, Qiuhong & Lev, Benjamin, 2020. "Cold chain transportation decision in the vaccine supply chain," European Journal of Operational Research, Elsevier, vol. 283(1), pages 182-195.
    7. Lin, Boqiang & Jia, Zhijie, 2018. "Impact of quota decline scheme of emission trading in China: A dynamic recursive CGE model," Energy, Elsevier, vol. 149(C), pages 190-203.
    8. Tang, Shaolong & Wang, Wenjie & Yan, Hong & Hao, Gang, 2015. "Low carbon logistics: Reducing shipment frequency to cut carbon emissions," International Journal of Production Economics, Elsevier, vol. 164(C), pages 339-350.
    9. Walter J. Bell & Louis M. Dalberto & Marshall L. Fisher & Arnold J. Greenfield & R. Jaikumar & Pradeep Kedia & Robert G. Mack & Paul J. Prutzman, 1983. "Improving the Distribution of Industrial Gases with an On-Line Computerized Routing and Scheduling Optimizer," Interfaces, INFORMS, vol. 13(6), pages 4-23, December.
    10. Guri Bang & David G. Victor & Steinar Andresen, 2017. "California’s Cap-and-Trade System: Diffusion and Lessons," Global Environmental Politics, MIT Press, vol. 17(3), pages 12-30, August.
    11. Haddadsisakht, Ali & Ryan, Sarah M., 2018. "Closed-loop supply chain network design with multiple transportation modes under stochastic demand and uncertain carbon tax," International Journal of Production Economics, Elsevier, vol. 195(C), pages 118-131.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ratko Stanković & Tomislav Pereglin & Tomislav Erdelić, 2023. "Optimizing Utilization of Transport Capacities in the Cold Chain by Introducing Dynamic Allocation of Semi-Trailers," Logistics, MDPI, vol. 7(4), pages 1-22, December.
    2. Shaojian Qu & Xinqi Li & Chang Liu & Xufeng Tang & Zhisheng Peng & Ying Ji, 2023. "Two-Stage Robust Programming Modeling for Continuous Berth Allocation with Uncertain Vessel Arrival Time," Sustainability, MDPI, vol. 15(13), pages 1-30, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yang, Yuxiang & Goodarzi, Shadi & Jabbarzadeh, Armin & Fahimnia, Behnam, 2022. "In-house production and outsourcing under different emissions reduction regulations: An equilibrium decision model for global supply chains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    2. Markov, Iliya & Bierlaire, Michel & Cordeau, Jean-François & Maknoon, Yousef & Varone, Sacha, 2018. "A unified framework for rich routing problems with stochastic demands," Transportation Research Part B: Methodological, Elsevier, vol. 114(C), pages 213-240.
    3. Hao Zou & Jin Qin & Xiaofeng Long, 2022. "Coordination Decisions for a Low-Carbon Supply Chain Considering Risk Aversion under Carbon Quota Policy," IJERPH, MDPI, vol. 19(5), pages 1-24, February.
    4. Wanting Chen & Zhi-Hua Hu, 2020. "Analysis of Multi-Stakeholders’ Behavioral Strategies Considering Public Participation under Carbon Taxes and Subsidies: An Evolutionary Game Approach," Sustainability, MDPI, vol. 12(3), pages 1-26, January.
    5. Ji, Ying & Du, Jianhui & Han, Xiaoya & Wu, Xiaoqing & Huang, Ripeng & Wang, Shilei & Liu, Zhimin, 2020. "A mixed integer robust programming model for two-echelon inventory routing problem of perishable products," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 548(C).
    6. Ouhimmou, Mustapha & Nourelfath, Mustapha & Bouchard, Mathieu & Bricha, Naji, 2019. "Design of robust distribution network under demand uncertainty: A case study in the pulp and paper," International Journal of Production Economics, Elsevier, vol. 218(C), pages 96-105.
    7. Shaojian Qu & Xinqi Li & Chang Liu & Xufeng Tang & Zhisheng Peng & Ying Ji, 2023. "Two-Stage Robust Programming Modeling for Continuous Berth Allocation with Uncertain Vessel Arrival Time," Sustainability, MDPI, vol. 15(13), pages 1-30, July.
    8. 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.
    9. Jianwen Ren & Yingqiang Xu & Shiyuan Wang, 2018. "A Distributed Robust Dispatch Approach for Interconnected Systems with a High Proportion of Wind Power Penetration," Energies, MDPI, vol. 11(4), pages 1-18, April.
    10. Chen, Huadun & Du, Qianxi & Huo, Tengfei & Liu, Peiran & Cai, Weiguang & Liu, Bingsheng, 2023. "Spatiotemporal patterns and driving mechanism of carbon emissions in China's urban residential building sector," Energy, Elsevier, vol. 263(PE).
    11. Wenqing Chen & Melvyn Sim & Jie Sun & Chung-Piaw Teo, 2010. "From CVaR to Uncertainty Set: Implications in Joint Chance-Constrained Optimization," Operations Research, INFORMS, vol. 58(2), pages 470-485, April.
    12. Zhi Chen & Melvyn Sim & Huan Xu, 2019. "Distributionally Robust Optimization with Infinitely Constrained Ambiguity Sets," Operations Research, INFORMS, vol. 67(5), pages 1328-1344, September.
    13. Stefan Mišković, 2017. "A VNS-LP algorithm for the robust dynamic maximal covering location problem," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(4), pages 1011-1033, October.
    14. Sarhadi, Hassan & Naoum-Sawaya, Joe & Verma, Manish, 2020. "A robust optimization approach to locating and stockpiling marine oil-spill response facilities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    15. Fang, Sheng & Lu, Xinsheng & Li, Jianfeng & Qu, Ling, 2018. "Multifractal detrended cross-correlation analysis of carbon emission allowance and stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 551-566.
    16. Li, Shukai & Liu, Ronghui & Yang, Lixing & Gao, Ziyou, 2019. "Robust dynamic bus controls considering delay disturbances and passenger demand uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 88-109.
    17. Chassein, André & Dokka, Trivikram & Goerigk, Marc, 2019. "Algorithms and uncertainty sets for data-driven robust shortest path problems," European Journal of Operational Research, Elsevier, vol. 274(2), pages 671-686.
    18. Akhtar Hussain & Van-Hai Bui & Hak-Man Kim, 2016. "Robust Optimization-Based Scheduling of Multi-Microgrids Considering Uncertainties," Energies, MDPI, vol. 9(4), pages 1-21, April.
    19. M. J. Naderi & M. S. Pishvaee, 2017. "Robust bi-objective macroscopic municipal water supply network redesign and rehabilitation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(9), pages 2689-2711, July.
    20. Kandpal, Bakul & Pareek, Parikshit & Verma, Ashu, 2022. "A robust day-ahead scheduling strategy for EV charging stations in unbalanced distribution grid," Energy, Elsevier, vol. 249(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:endesu:v:23:y:2021:i:9:d:10.1007_s10668-021-01236-z. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.