IDEAS home Printed from https://ideas.repec.org/a/wut/journl/v1y2017p21-41id1267.html
   My bibliography  Save this article

Robust bi-level optimization for an opportunistic supply chain network design problem in an uncertain and risky environment

Author

Listed:
  • Hêris Golpîra

Abstract

This paper introduces the problem of designing a single-product supply chain network in an agile manufacturing setting under a vendor managed inventory (VMI) strategy to seize a new market opportunity. The problem addresses the level of risk aversion of the retailer when dealing with the uncertainty of market related information through a conditional value at risk (CVaR) approach. This approach leads to a bilevel programming problem. The Karush–Kuhn–Tucker (KKT) conditions are employed to transform the model into a single-level, mixed-integer linear programming problem by considering some relaxations. Since realizations of imprecisely known parameters are the only information available, a data-driven approach is employed as a suitable, more practical, methodology of avoiding distributional assumptions. Finally, the effectiveness of the proposed model is demonstrated through a numerical example.

Suggested Citation

  • Hêris Golpîra, 2017. "Robust bi-level optimization for an opportunistic supply chain network design problem in an uncertain and risky environment," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 27(1), pages 21-41.
  • Handle: RePEc:wut:journl:v:1:y:2017:p:21-41:id:1267
    DOI: 10.5277/ord170102
    as

    Download full text from publisher

    File URL: https://ord.pwr.edu.pl/assets/papers_archive/1267%20-%20published.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.5277/ord170102?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
    ---><---

    References listed on IDEAS

    as
    1. Bilge Bilgen & Yelda Çelebi, 2013. "Integrated production scheduling and distribution planning in dairy supply chain by hybrid modelling," Annals of Operations Research, Springer, vol. 211(1), pages 55-82, December.
    2. Kostis Taxakis & Chrissoleon Papadopoulos, 2016. "A design model and a production–distribution and inventory planning model in multi-product supply chain networks," International Journal of Production Research, Taylor & Francis Journals, vol. 54(21), pages 6436-6457, November.
    3. Qin, Yan & Wang, Ruoxuan & Vakharia, Asoo J. & Chen, Yuwen & Seref, Michelle M.H., 2011. "The newsvendor problem: Review and directions for future research," European Journal of Operational Research, Elsevier, vol. 213(2), pages 361-374, September.
    4. Karthik Natarajan & Dessislava Pachamanova & Melvyn Sim, 2009. "Constructing Risk Measures from Uncertainty Sets," Operations Research, INFORMS, vol. 57(5), pages 1129-1141, October.
    5. 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.
    6. S S Chauhan & J-M Proth & A M Sarmiento & R Nagi, 2006. "Opportunistic supply chain formation from qualified partners for a new market demand," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(9), pages 1089-1099, September.
    7. Pan, Feng & Nagi, Rakesh, 2013. "Multi-echelon supply chain network design in agile manufacturing," Omega, Elsevier, vol. 41(6), pages 969-983.
    8. Heckmann, Iris & Comes, Tina & Nickel, Stefan, 2015. "A critical review on supply chain risk – Definition, measure and modeling," Omega, Elsevier, vol. 52(C), pages 119-132.
    9. Morteza Lalmazloumian & Kuan Yew Wong & Kannan Govindan & Devika Kannan, 2016. "A robust optimization model for agile and build-to-order supply chain planning under uncertainties," Annals of Operations Research, Springer, vol. 240(2), pages 435-470, May.
    10. Gotoh, Jun-ya & Takano, Yuichi, 2007. "Newsvendor solutions via conditional value-at-risk minimization," European Journal of Operational Research, Elsevier, vol. 179(1), pages 80-96, May.
    11. 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.
    12. Dimitris Bertsimas & David B. Brown, 2009. "Constructing Uncertainty Sets for Robust Linear Optimization," Operations Research, INFORMS, vol. 57(6), pages 1483-1495, December.
    13. Wu, Meng & Zhu, Stuart X. & Teunter, Ruud H., 2013. "The risk-averse newsvendor problem with random capacity," European Journal of Operational Research, Elsevier, vol. 231(2), pages 328-336.
    14. Liu, Songsong & Papageorgiou, Lazaros G., 2013. "Multiobjective optimisation of production, distribution and capacity planning of global supply chains in the process industry," Omega, Elsevier, vol. 41(2), pages 369-382.
    15. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    16. Kopanos, Georgios M. & Puigjaner, Luis & Georgiadis, Michael C., 2012. "Simultaneous production and logistics operations planning in semicontinuous food industries," Omega, Elsevier, vol. 40(5), pages 634-650.
    17. Chahar, Kiran & Taaffe, Kevin, 2009. "Risk averse demand selection with all-or-nothing orders," Omega, Elsevier, vol. 37(5), pages 996-1006, October.
    18. Kang, Jae-Hun & Kim, Yeong-Dae, 2012. "Inventory control in a two-level supply chain with risk pooling effect," International Journal of Production Economics, Elsevier, vol. 135(1), pages 116-124.
    19. Yu, Min & Nagurney, Anna, 2013. "Competitive food supply chain networks with application to fresh produce," European Journal of Operational Research, Elsevier, vol. 224(2), pages 273-282.
    20. 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.
    Full references (including those not matched with items on IDEAS)

    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. Behzadi, Golnar & O’Sullivan, Michael Justin & Olsen, Tava Lennon & Zhang, Abraham, 2018. "Agribusiness supply chain risk management: A review of quantitative decision models," Omega, Elsevier, vol. 79(C), pages 21-42.
    2. 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.
    3. Selim Mankai & Khaled Guesmi, 2014. "Robust Portfolio Protection: A Scenarios-Based Approach," Working Papers hal-04141326, HAL.
    4. 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.
    5. 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.
    6. 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.
    7. Andrew J. Keith & Darryl K. Ahner, 2021. "A survey of decision making and optimization under uncertainty," Annals of Operations Research, Springer, vol. 300(2), pages 319-353, May.
    8. 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.
    9. Alireza Ghahtarani & Ahmed Saif & Alireza Ghasemi, 2022. "Robust portfolio selection problems: a comprehensive review," Operational Research, Springer, vol. 22(4), pages 3203-3264, September.
    10. Alireza Ghahtarani & Ahmed Saif & Alireza Ghasemi, 2021. "Robust Portfolio Selection Problems: A Comprehensive Review," Papers 2103.13806, arXiv.org, revised Jan 2022.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. Claire Nicolas & Stéphane Tchung-Ming & Emmanuel Hache, 2016. "Energy transition in transportation under cost uncertainty, an assessment based on robust optimization," Working Papers hal-02475943, HAL.
    16. 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.
    17. 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.
    18. Calvete, Herminia I. & Galé, Carmen & Iranzo, José A., 2014. "Planning of a decentralized distribution network using bilevel optimization," Omega, Elsevier, vol. 49(C), pages 30-41.
    19. Lin, Jun & Ng, Tsan Sheng, 2011. "Robust multi-market newsvendor models with interval demand data," European Journal of Operational Research, Elsevier, vol. 212(2), pages 361-373, July.
    20. Gabrel, Virginie & Murat, Cécile & Thiele, Aurélie, 2014. "Recent advances in robust optimization: An overview," European Journal of Operational Research, Elsevier, vol. 235(3), pages 471-483.

    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:wut:journl:v:1:y:2017:p:21-41:id:1267. 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: Adam Kasperski (email available below). General contact details of provider: https://edirc.repec.org/data/iopwrpl.html .

    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.