IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i21p5928-d280068.html
   My bibliography  Save this article

A p -Robust Green Supply Chain Network Design Model under Uncertain Carbon Price and Demand

Author

Listed:
  • Ruozhen Qiu

    (School of Business Administration, Northeastern University, Shenyang 110169, China)

  • Shunpeng Shi

    (School of Business Administration, Northeastern University, Shenyang 110169, China)

  • Yue Sun

    (School of Business Administration, Northeastern University, Shenyang 110169, China)

Abstract

The problem of designing a multi-product, multi-period green supply chain network under uncertainties in carbon price and customer demand is studied in this paper. The purpose of this study is to develop a robust green supply chain network design model to minimize the total cost and to effectively cope with uncertainties. A scenario tree method is applied to model the uncertainty, and a green supply chain network design model is developed under the p -robustness criterion. Furthermore, the solution method for determining the lower and upper bounds of the relative regret limit is introduced, which is convenient for decision-makers to choose the corresponding supply chain network structure through the tradeoff between risk and cost performance. In particular, to overcome the large scale of the model caused by a high number of uncertain scenarios and reduce the computational difficulty, a scenario reduction technique is applied to filter the scenarios. Numerical calculations are executed to analyze the influence of relevant parameters on the performance of the designed green supply chain network. The results show that the proposed p -robust green supply chain network design model can effectively deal with carbon and demand uncertainties while ensuring cost performance, and can offer more choices for decision-makers with different risk preferences.

Suggested Citation

  • Ruozhen Qiu & Shunpeng Shi & Yue Sun, 2019. "A p -Robust Green Supply Chain Network Design Model under Uncertain Carbon Price and Demand," Sustainability, MDPI, vol. 11(21), pages 1-22, October.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:21:p:5928-:d:280068
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/21/5928/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/11/21/5928/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Aliakbar Hasani & Seyed Hessameddin Zegordi & Ehsan Nikbakhsh, 2015. "Robust closed-loop global supply chain network design under uncertainty: the case of the medical device industry," International Journal of Production Research, Taylor & Francis Journals, vol. 53(5), pages 1596-1624, March.
    2. Ahmad Rezaee & Farzad Dehghanian & Behnam Fahimnia & Benita Beamon, 2017. "Green supply chain network design with stochastic demand and carbon price," Annals of Operations Research, Springer, vol. 250(2), pages 463-485, March.
    3. Waltho, Cynthia & Elhedhli, Samir & Gzara, Fatma, 2019. "Green supply chain network design: A review focused on policy adoption and emission quantification," International Journal of Production Economics, Elsevier, vol. 208(C), pages 305-318.
    4. Baghalian, Atefeh & Rezapour, Shabnam & Farahani, Reza Zanjirani, 2013. "Robust supply chain network design with service level against disruptions and demand uncertainties: A real-life case," European Journal of Operational Research, Elsevier, vol. 227(1), pages 199-215.
    5. Nickel, Stefan & Saldanha-da-Gama, Francisco & Ziegler, Hans-Peter, 2012. "A multi-stage stochastic supply network design problem with financial decisions and risk management," Omega, Elsevier, vol. 40(5), pages 511-524.
    6. Tsai Chi Kuo & Yile Lee, 2019. "Using Pareto Optimization to Support Supply Chain Network Design within Environmental Footprint Impact Assessment," Sustainability, MDPI, vol. 11(2), pages 1-13, January.
    7. Gang Wang & Angappa Gunasekaran & Eric W. T. Ngai, 2018. "Distribution network design with big data: model and analysis," Annals of Operations Research, Springer, vol. 270(1), pages 539-551, November.
    8. Junfeng Tian & Jinfeng Yue, 2014. "Bounds of Relative Regret Limit in p-Robust Supply Chain Network Design," Production and Operations Management, Production and Operations Management Society, vol. 23(10), pages 1811-1831, October.
    9. Bandar Alkhayyal, 2019. "Corporate Social Responsibility Practices in the U.S.: Using Reverse Supply Chain Network Design and Optimization Considering Carbon Cost," Sustainability, MDPI, vol. 11(7), pages 1-22, April.
    10. Pimentel, Bruno S. & Mateus, Geraldo R. & Almeida, Franklin A., 2013. "Stochastic capacity planning and dynamic network design," International Journal of Production Economics, Elsevier, vol. 145(1), pages 139-149.
    11. Fattahi, Mohammad & Govindan, Kannan & Keyvanshokooh, Esmaeil, 2017. "Responsive and resilient supply chain network design under operational and disruption risks with delivery lead-time sensitive customers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 101(C), pages 176-200.
    12. Xu, Xiaofeng & Wei, Zhifei & Ji, Qiang & Wang, Chenglong & Gao, Guowei, 2019. "Global renewable energy development: Influencing factors, trend predictions and countermeasures," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    13. Fahimnia, Behnam & Sarkis, Joseph & Choudhary, Alok & Eshragh, Ali, 2015. "Tactical supply chain planning under a carbon tax policy scheme: A case study," International Journal of Production Economics, Elsevier, vol. 164(C), pages 206-215.
    14. Zakeri, Atefe & Dehghanian, Farzad & Fahimnia, Behnam & Sarkis, Joseph, 2015. "Carbon pricing versus emissions trading: A supply chain planning perspective," International Journal of Production Economics, Elsevier, vol. 164(C), pages 197-205.
    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. Marta Negri & Enrico Cagno & Claudia Colicchia & Joseph Sarkis, 2021. "Integrating sustainability and resilience in the supply chain: A systematic literature review and a research agenda," Business Strategy and the Environment, Wiley Blackwell, vol. 30(7), pages 2858-2886, November.

    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. Jahani, Hamed & Abbasi, Babak & Sheu, Jiuh-Biing & Klibi, Walid, 2024. "Supply chain network design with financial considerations: A comprehensive review," European Journal of Operational Research, Elsevier, vol. 312(3), pages 799-839.
    2. Yuki Kinoshita & Takaki Nagao & Hiromasa Ijuin & Keisuke Nagasawa & Tetsuo Yamada & Surendra M. Gupta, 2023. "Utilization of Free Trade Agreements to Minimize Costs and Carbon Emissions in the Global Supply Chain for Sustainable Logistics," Logistics, MDPI, vol. 7(2), pages 1-21, June.
    3. Sina Abbasi & Babek Erdebilli, 2023. "Green Closed-Loop Supply Chain Networks’ Response to Various Carbon Policies during COVID-19," Sustainability, MDPI, vol. 15(4), pages 1-30, February.
    4. Hongtao Ren & Wenji Zhou & Marek Makowski & Hongbin Yan & Yadong Yu & Tieju Ma, 2021. "Incorporation of life cycle emissions and carbon price uncertainty into the supply chain network management of PVC production," Annals of Operations Research, Springer, vol. 300(2), pages 601-620, May.
    5. Meng, Xiaoge & Yao, Zhong & Nie, Jiajia & Zhao, Yingxue & Li, Zenglu, 2018. "Low-carbon product selection with carbon tax and competition: Effects of the power structure," International Journal of Production Economics, Elsevier, vol. 200(C), pages 224-230.
    6. Blossey, Gregor & Hahn, Gerd J. & Koberstein, Achim, 2022. "Planning pharmaceutical manufacturing networks in the light of uncertain production approval times," International Journal of Production Economics, Elsevier, vol. 244(C).
    7. Ahmad Rezaee & Farzad Dehghanian & Behnam Fahimnia & Benita Beamon, 2017. "Green supply chain network design with stochastic demand and carbon price," Annals of Operations Research, Springer, vol. 250(2), pages 463-485, March.
    8. Fattahi, Mohammad & Govindan, Kannan & Keyvanshokooh, Esmaeil, 2017. "Responsive and resilient supply chain network design under operational and disruption risks with delivery lead-time sensitive customers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 101(C), pages 176-200.
    9. Gaigné, C. & Hovelaque, V. & Mechouar, Y., 2020. "Carbon tax and sustainable facility location: The role of production technology," International Journal of Production Economics, Elsevier, vol. 224(C).
    10. Zhitao Xu & Adel Elomri & Shaligram Pokharel & Fatih Mutlu, 2019. "The Design of Green Supply Chains under Carbon Policies: A Literature Review of Quantitative Models," Sustainability, MDPI, vol. 11(11), pages 1-20, May.
    11. Fahimnia, Behnam & Jabbarzadeh, Armin, 2016. "Marrying supply chain sustainability and resilience: A match made in heaven," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 91(C), pages 306-324.
    12. Tosarkani, Babak Mohamadpour & Amin, Saman Hassanzadeh & Zolfagharinia, Hossein, 2020. "A scenario-based robust possibilistic model for a multi-objective electronic reverse logistics network," International Journal of Production Economics, Elsevier, vol. 224(C).
    13. Zhou, Xiaoyang & Wei, Xiaoya & Lin, Jun & Tian, Xin & Lev, Benjamin & Wang, Shouyang, 2021. "Supply chain management under carbon taxes: A review and bibliometric analysis," Omega, Elsevier, vol. 98(C).
    14. Ozgur Kabadurmus & Mehmet S. Erdogan, 2020. "Sustainable, multimodal and reliable supply chain design," Annals of Operations Research, Springer, vol. 292(1), pages 47-70, September.
    15. Nayeri, Sina & Sazvar, Zeinab & Heydari, Jafar, 2022. "A global-responsive supply chain considering sustainability and resiliency: Application in the medical devices industry," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    16. Govindan, Kannan & Fattahi, Mohammad, 2017. "Investigating risk and robustness measures for supply chain network design under demand uncertainty: A case study of glass supply chain," International Journal of Production Economics, Elsevier, vol. 183(PC), pages 680-699.
    17. Rena Kondo & Yuki Kinoshita & Tetsuo Yamada, 2019. "Green Procurement Decisions with Carbon Leakage by Global Suppliers and Order Quantities under Different Carbon Tax," Sustainability, MDPI, vol. 11(13), pages 1-19, July.
    18. M. Fattahi & M. Mahootchi & S. M. Moattar Husseini, 2016. "Integrated strategic and tactical supply chain planning with price-sensitive demands," Annals of Operations Research, Springer, vol. 242(2), pages 423-456, July.
    19. Hasani, Aliakbar & Khosrojerdi, Amirhossein, 2016. "Robust global supply chain network design under disruption and uncertainty considering resilience strategies: A parallel memetic algorithm for a real-life case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 87(C), pages 20-52.
    20. Longinidis, Pantelis & Georgiadis, Michael C., 2014. "Integration of sale and leaseback in the optimal design of supply chain networks," Omega, Elsevier, vol. 47(C), pages 73-89.

    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:gam:jsusta:v:11:y:2019:i:21:p:5928-:d:280068. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.