IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v257y2017i1d10.1007_s10479-014-1756-6.html
   My bibliography  Save this article

Robust supply chain network design: an optimization model with real world application

Author

Listed:
  • Shiva Zokaee

    (Iran University of Science and Technology)

  • Armin Jabbarzadeh

    (Iran University of Science and Technology)

  • Behnam Fahimnia

    (The University of Sydney Business School)

  • Seyed Jafar Sadjadi

    (Iran University of Science and Technology)

Abstract

This paper presents a robust optimization model for the design of a supply chain facing uncertainty in demand, supply capacity and major cost data including transportation and shortage cost parameters. We first present a base model that aims to determine the strategic ‘location’ and tactical ‘allocation’ decisions for a deterministic four-tier supply chain. The model is then extended to incorporate uncertainty in key input parameters using a robust optimization approach that can overcome the limitations of scenario-based solution methods in a tractable way, i.e. without excessive changes in complexity of the underlying base deterministic model. The application of the approach is investigated in an actual case study where real data is utilized to design a bread supply chain network. Numerical results obtained from model implementation and sensitivity analysis experiments arrive at important managerial insights and practical implications.

Suggested Citation

  • Shiva Zokaee & Armin Jabbarzadeh & Behnam Fahimnia & Seyed Jafar Sadjadi, 2017. "Robust supply chain network design: an optimization model with real world application," Annals of Operations Research, Springer, vol. 257(1), pages 15-44, October.
    • Handle: RePEc:spr:annopr:v:257:y:2017:i:1:d:10.1007_s10479-014-1756-6
    DOI: 10.1007/s10479-014-1756-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-014-1756-6
    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/s10479-014-1756-6?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. Jean-François Cordeau & Federico Pasin & Marius Solomon, 2006. "An integrated model for logistics network design," Annals of Operations Research, Springer, vol. 144(1), pages 59-82, April.
    2. Tang, Christopher S., 2006. "Perspectives in supply chain risk management," International Journal of Production Economics, Elsevier, vol. 103(2), pages 451-488, October.
    3. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    4. Azaron, A. & Brown, K.N. & Tarim, S.A. & Modarres, M., 2008. "A multi-objective stochastic programming approach for supply chain design considering risk," International Journal of Production Economics, Elsevier, vol. 116(1), pages 129-138, November.
    5. Najafi, Mehdi & Eshghi, Kourosh & Dullaert, Wout, 2013. "A multi-objective robust optimization model for logistics planning in the earthquake response phase," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 49(1), pages 217-249.
    6. Georgiadis, Michael C. & Tsiakis, Panagiotis & Longinidis, Pantelis & Sofioglou, Maria K., 2011. "Optimal design of supply chain networks under uncertain transient demand variations," Omega, Elsevier, vol. 39(3), pages 254-272, June.
    7. Jabbarzadeh, Armin & Fahimnia, Behnam & Seuring, Stefan, 2014. "Dynamic supply chain network design for the supply of blood in disasters: A robust model with real world application," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 225-244.
    8. Ben-Tal, Aharon & Chung, Byung Do & Mandala, Supreet Reddy & Yao, Tao, 2011. "Robust optimization for emergency logistics planning: Risk mitigation in humanitarian relief supply chains," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1177-1189, September.
    9. Dimitris Bertsimas & Aurélie Thiele, 2006. "A Robust Optimization Approach to Inventory Theory," Operations Research, INFORMS, vol. 54(1), pages 150-168, February.
    10. ,, 2000. "Problems And Solutions," Econometric Theory, Cambridge University Press, vol. 16(2), pages 287-299, April.
    11. Yu, Chian-Son & Li, Han-Lin, 2000. "A robust optimization model for stochastic logistic problems," International Journal of Production Economics, Elsevier, vol. 64(1-3), pages 385-397, March.
    12. Xin Chen & Yuhan Zhang, 2009. "Uncertain Linear Programs: Extended Affinely Adjustable Robust Counterparts," Operations Research, INFORMS, vol. 57(6), pages 1469-1482, December.
    13. A. L. Soyster, 1973. "Technical Note—Convex Programming with Set-Inclusive Constraints and Applications to Inexact Linear Programming," Operations Research, INFORMS, vol. 21(5), pages 1154-1157, October.
    14. X. M. Hu & D. Ralph, 2004. "Convergence of a Penalty Method for Mathematical Programming with Complementarity Constraints," Journal of Optimization Theory and Applications, Springer, vol. 123(2), pages 365-390, November.
    15. Klibi, Walid & Martel, Alain & Guitouni, Adel, 2010. "The design of robust value-creating supply chain networks: A critical review," European Journal of Operational Research, Elsevier, vol. 203(2), pages 283-293, June.
    16. John M. Mulvey & Robert J. Vanderbei & Stavros A. Zenios, 1995. "Robust Optimization of Large-Scale Systems," Operations Research, INFORMS, vol. 43(2), pages 264-281, April.
    17. Melo, M.T. & Nickel, S. & Saldanha-da-Gama, F., 2009. "Facility location and supply chain management - A review," European Journal of Operational Research, Elsevier, vol. 196(2), pages 401-412, July.
    18. Mirzapour Al-e-hashem, S.M.J. & Malekly, H. & Aryanezhad, M.B., 2011. "A multi-objective robust optimization model for multi-product multi-site aggregate production planning in a supply chain under uncertainty," International Journal of Production Economics, Elsevier, vol. 134(1), pages 28-42, November.
    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. Seyyed-Mahdi Hosseini-Motlagh & Mohammad Reza Ghatreh Samani & Firoozeh Abbasi Saadi, 2021. "Strategic optimization of wheat supply chain network under uncertainty: a real case study," Operational Research, Springer, vol. 21(3), pages 1487-1527, September.
    2. Aghajani, Mojtaba & Ali Torabi, S. & Altay, Nezih, 2023. "Resilient relief supply planning using an integrated procurement-warehousing model under supply disruption," Omega, Elsevier, vol. 118(C).
    3. Dezhi Zhang & Shuxin Yang & Shuangyan Li & Jiajun Fan & Bin Ji, 2020. "Integrated Optimization of the Location–Inventory Problem of Maintenance Component Distribution for High-Speed Railway Operations," Sustainability, MDPI, vol. 12(13), pages 1-25, July.
    4. Mohammad Fattahi, 2020. "A data-driven approach for supply chain network design under uncertainty with consideration of social concerns," Annals of Operations Research, Springer, vol. 288(1), pages 265-284, May.
    5. Li, Yuchen & Zhang, Jianghua & Yu, Guodong, 2020. "A scenario-based hybrid robust and stochastic approach for joint planning of relief logistics and casualty distribution considering secondary disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    6. Almaraj, Ismail I. & Trafalis, Theodore B., 2019. "An integrated multi-echelon robust closed- loop supply chain under imperfect quality production," International Journal of Production Economics, Elsevier, vol. 218(C), pages 212-227.
    7. Reza Ramezanian & Sadjad Khalesi, 2021. "Integration of multi-product supply chain network design and assembly line balancing," Operational Research, Springer, vol. 21(1), pages 453-483, March.
    8. Aijun Liu & Yan Zhang & Senhao Luo & Jie Miao, 2020. "Dual-Channel Global Closed-Loop Supply Chain Network Optimization Based on Random Demand and Recovery Rate," IJERPH, MDPI, vol. 17(23), pages 1-32, November.
    9. Diabat, Ali & Jabbarzadeh, Armin & Khosrojerdi, Amir, 2019. "A perishable product supply chain network design problem with reliability and disruption considerations," International Journal of Production Economics, Elsevier, vol. 212(C), pages 125-138.
    10. Lin Chen & Ting Dong & Jin Peng & Dan Ralescu, 2023. "Uncertainty Analysis and Optimization Modeling with Application to Supply Chain Management: A Systematic Review," Mathematics, MDPI, vol. 11(11), pages 1-45, May.
    11. Ge He & Li Zhou & Yiyang Dai & Yagu Dang & Xu Ji, 2020. "Coal Industrial Supply Chain Network and Associated Evaluation Models," Sustainability, MDPI, vol. 12(23), pages 1-20, November.
    12. Ali Ala & Morteza Yazdani & Mohsen Ahmadi & Aida Poorianasab & Mahdi Yousefi Nejad Attari, 2023. "An efficient healthcare chain design for resolving the patient scheduling problem: queuing theory and MILP-ASA optimization approach," Annals of Operations Research, Springer, vol. 328(1), pages 3-33, September.
    13. Schreiber, Lucas & Jarmer, Jan-Philipp & Kamphues, Josef, 2020. "Energy-efficient supply chain design: Data aggregation and processing," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Jahn, Carlos & Kersten, Wolfgang & Ringle, Christian M. (ed.), Data Science in Maritime and City Logistics: Data-driven Solutions for Logistics and Sustainability. Proceedings of the Hamburg International Conferen, volume 30, pages 129-155, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    14. Mohammad Ali Raayatpanah & Thomas Weise & Jinsong Wu & Ming Tan & Panos M. Pardalos, 2023. "Robust optimization for minimizing energy consumption of multicast transmissions in coded wireless packet networks under distance uncertainty," Journal of Combinatorial Optimization, Springer, vol. 46(1), pages 1-29, August.
    15. Mohammad Reza Ghatreh Samani & Seyyed-Mahdi Hosseini-Motlagh, 2019. "An enhanced procedure for managing blood supply chain under disruptions and uncertainties," Annals of Operations Research, Springer, vol. 283(1), pages 1413-1462, December.
    16. Jabbarzadeh, Armin & Haughton, Michael & Pourmehdi, Fahime, 2019. "A robust optimization model for efficient and green supply chain planning with postponement strategy," International Journal of Production Economics, Elsevier, vol. 214(C), pages 266-283.
    17. Fahimnia, Behnam & Jabbarzadeh, Armin & Sarkis, Joseph, 2018. "Greening versus resilience: A supply chain design perspective," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 119(C), pages 129-148.
    18. Fatemeh Keshavarz-Ghorbani & Seyed Hamid Reza Pasandideh, 2022. "A Lagrangian relaxation algorithm for optimizing a bi-objective agro-supply chain model considering CO2 emissions," Annals of Operations Research, Springer, vol. 314(2), pages 497-527, 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. Mohammaddust, Faeghe & Rezapour, Shabnam & Farahani, Reza Zanjirani & Mofidfar, Mohammad & Hill, Alex, 2017. "Developing lean and responsive supply chains: A robust model for alternative risk mitigation strategies in supply chain designs," International Journal of Production Economics, Elsevier, vol. 183(PC), pages 632-653.
    2. Almaraj, Ismail I. & Trafalis, Theodore B., 2019. "An integrated multi-echelon robust closed- loop supply chain under imperfect quality production," International Journal of Production Economics, Elsevier, vol. 218(C), pages 212-227.
    3. Roberto Gomes de Mattos & Fabricio Oliveira & Adriana Leiras & Abdon Baptista de Paula Filho & Paulo Gonçalves, 2019. "Robust optimization of the insecticide-treated bed nets procurement and distribution planning under uncertainty for malaria prevention and control," Annals of Operations Research, Springer, vol. 283(1), pages 1045-1078, December.
    4. Javid Jouzdani & Mohammad Fathian & Ahmad Makui & Mehdi Heydari, 2020. "Robust design and planning for a multi-mode multi-product supply network: a dairy industry case study," Operational Research, Springer, vol. 20(3), pages 1811-1840, September.
    5. Bairamzadeh, Samira & Saidi-Mehrabad, Mohammad & Pishvaee, Mir Saman, 2018. "Modelling different types of uncertainty in biofuel supply network design and planning: A robust optimization approach," Renewable Energy, Elsevier, vol. 116(PA), pages 500-517.
    6. Ghazaleh Ahmadi & Reza Tavakkoli-Moghaddam & Armand Baboli & Mehdi Najafi, 2022. "A decision support model for robust allocation and routing of search and rescue resources after earthquake: a case study," Operational Research, Springer, vol. 22(2), pages 1039-1081, April.
    7. 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.
    8. Jabbarzadeh, Armin & Haughton, Michael & Pourmehdi, Fahime, 2019. "A robust optimization model for efficient and green supply chain planning with postponement strategy," International Journal of Production Economics, Elsevier, vol. 214(C), pages 266-283.
    9. Hashem Omrani & Farzane Adabi & Narges Adabi, 2017. "Designing an efficient supply chain network with uncertain data: a robust optimization—data envelopment analysis approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(7), pages 816-828, July.
    10. Antonio G. Martín & Manuel Díaz-Madroñero & Josefa Mula, 2020. "Master production schedule using robust optimization approaches in an automobile second-tier supplier," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(1), pages 143-166, March.
    11. Jabbarzadeh, Armin & Fahimnia, Behnam & Sheu, Jiuh-Biing & Moghadam, Hani Shahmoradi, 2016. "Designing a supply chain resilient to major disruptions and supply/demand interruptions," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 121-149.
    12. Oğuz Solyalı & Jean-François Cordeau & Gilbert Laporte, 2016. "The Impact of Modeling on Robust Inventory Management Under Demand Uncertainty," Management Science, INFORMS, vol. 62(4), pages 1188-1201, April.
    13. Gilani, Hani & Sahebi, Hadi, 2022. "A data-driven robust optimization model by cutting hyperplanes on vaccine access uncertainty in COVID-19 vaccine supply chain," Omega, Elsevier, vol. 110(C).
    14. Cleber D. Rocco & Reinaldo Morabito, 2016. "Robust optimisation approach applied to the analysis of production / logistics and crop planning in the tomato processing industry," International Journal of Production Research, Taylor & Francis Journals, vol. 54(19), pages 5842-5861, October.
    15. Sahling, Florian & Kayser, Ariane, 2016. "Strategic supply network planning with vendor selection under consideration of risk and demand uncertainty," Omega, Elsevier, vol. 59(PB), pages 201-214.
    16. 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.
    17. Jabbarzadeh, Armin & Fahimnia, Behnam & Seuring, Stefan, 2014. "Dynamic supply chain network design for the supply of blood in disasters: A robust model with real world application," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 225-244.
    18. Andreas Thorsen & Tao Yao, 2017. "Robust inventory control under demand and lead time uncertainty," Annals of Operations Research, Springer, vol. 257(1), pages 207-236, October.
    19. 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.
    20. Surya Prakash & Sameer Kumar & Gunjan Soni & Vipul Jain & Ajay Pal Singh Rathore, 2020. "Closed-loop supply chain network design and modelling under risks and demand uncertainty: an integrated robust optimization approach," Annals of Operations Research, Springer, vol. 290(1), pages 837-864, July.

    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:annopr:v:257:y:2017:i:1:d:10.1007_s10479-014-1756-6. 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.