IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2018i9p3099-d166793.html
   My bibliography  Save this article

An Improved Voronoi-Diagram-Based Algorithm for Continuous Facility Location Problem under Disruptions

Author

Listed:
  • Jiguang Wang

    (School of Economics & Management, Shanxi University, Taiyuan 030006, China)

  • Yucai Wu

    (School of Economics & Management, Shanxi University, Taiyuan 030006, China)

Abstract

The classical location models implicitly assume that the facilities, once built, will always operate as planned. However, some of the facilities may become unavailable from time to time due to disruptions which highlight the urgent need to effectively manage supply chain disruptions in spite of their low probability of occurrence. Therefore, it is critical to take account of disruptions when designing a resilient supply chain network so that it performs well as a whole even after an accidental disruption. In this paper, a stylized facility location problem is considered in a continuous plane which is solved through an improved Voronoi-diagram-based algorithm under disruption risks. The research problem is to minimize the total cost in normal and failure scenarios. Furthermore, the impact of misestimating the disruption probability is also investigated. The results numerically show that although the estimated disruption probability has a significant impact on the facilities configuration, it has a minor impact on the total quantity of facilities and the expected total cost. Therefore, this paper proposes that the decision-maker should moderately overestimate disruption risk based on the “pessimistic principle”. Finally, the conclusion considers managerial insights and proposes potential areas for future research.

Suggested Citation

  • Jiguang Wang & Yucai Wu, 2018. "An Improved Voronoi-Diagram-Based Algorithm for Continuous Facility Location Problem under Disruptions," Sustainability, MDPI, vol. 10(9), pages 1-13, August.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:9:p:3099-:d:166793
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/9/3099/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/10/9/3099/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wagner, Stephan M. & Neshat, Nikrouz, 2010. "Assessing the vulnerability of supply chains using graph theory," International Journal of Production Economics, Elsevier, vol. 126(1), pages 121-129, July.
    2. Tingting Cui & Yanfeng Ouyang & Zuo-Jun Max Shen, 2010. "Reliable Facility Location Design Under the Risk of Disruptions," Operations Research, INFORMS, vol. 58(4-part-1), pages 998-1011, August.
    3. Sawik, Tadeusz, 2015. "On the fair optimization of cost and customer service level in a supply chain under disruption risks," Omega, Elsevier, vol. 53(C), pages 58-66.
    4. Ruiying Li & Qiang Dong & Chong Jin & Rui Kang, 2017. "A New Resilience Measure for Supply Chain Networks," Sustainability, MDPI, vol. 9(1), pages 1-19, January.
    5. 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.
    6. Chen, Kebing & Xiao, Tiaojun, 2009. "Demand disruption and coordination of the supply chain with a dominant retailer," European Journal of Operational Research, Elsevier, vol. 197(1), pages 225-234, August.
    7. Wang, Xin & Ouyang, Yanfeng, 2013. "A continuum approximation approach to competitive facility location design under facility disruption risks," Transportation Research Part B: Methodological, Elsevier, vol. 50(C), pages 90-103.
    8. Tong Shu & Xiaoqin Gao & Shou Chen & Shouyang Wang & Kin Keung Lai & Lu Gan, 2016. "Weighing Efficiency-Robustness in Supply Chain Disruption by Multi-Objective Firefly Algorithm," Sustainability, MDPI, vol. 8(3), pages 1-27, March.
    9. Brian Tomlin, 2006. "On the Value of Mitigation and Contingency Strategies for Managing Supply Chain Disruption Risks," Management Science, INFORMS, vol. 52(5), pages 639-657, May.
    10. Yun, Lifen & Qin, Yong & Fan, Hongqiang & Ji, Changxu & Li, Xiaopeng & Jia, Limin, 2015. "A reliability model for facility location design under imperfect information," Transportation Research Part B: Methodological, Elsevier, vol. 81(P2), pages 596-615.
    11. Lawrence V. Snyder & Mark S. Daskin, 2005. "Reliability Models for Facility Location: The Expected Failure Cost Case," Transportation Science, INFORMS, vol. 39(3), pages 400-416, August.
    12. Li, Xiaopeng & Ouyang, Yanfeng, 2010. "A continuum approximation approach to reliable facility location design under correlated probabilistic disruptions," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 535-548, May.
    13. Michael K. Lim & Achal Bassamboo & Sunil Chopra & Mark S. Daskin, 2013. "Facility Location Decisions with Random Disruptions and Imperfect Estimation," Manufacturing & Service Operations Management, INFORMS, vol. 15(2), pages 239-249, May.
    14. Cui, Tingting & Ouyang, Yanfeng & Shen, Zuo-Jun Max J, 2010. "Reliable Facility Location Design under the Risk of Disruptions," University of California Transportation Center, Working Papers qt5sh2c7pw, University of California Transportation Center.
    15. Lawrence V. Snyder & Zümbül Atan & Peng Peng & Ying Rong & Amanda J. Schmitt & Burcu Sinsoysal, 2016. "OR/MS models for supply chain disruptions: a review," IISE Transactions, Taylor & Francis Journals, vol. 48(2), pages 89-109, February.
    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. Jiguang Wang & Yucai Wu, 2019. "A Continuous Approximation Approach Based on Regular Hexagon Partition for the Facility Location Problem under Disruptions Risk," Complexity, Hindawi, vol. 2019, pages 1-12, February.
    2. Antonio Zavala-Alcívar & María-José Verdecho & Juan-José Alfaro-Saiz, 2020. "A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain," Sustainability, MDPI, vol. 12(16), pages 1-38, August.
    3. Xiao Zhao & Xuhui Xia & Lei Wang & Guodong Yu, 2018. "Risk-Averse Facility Location for Green Closed-Loop Supply Chain Networks Design under Uncertainty," Sustainability, MDPI, vol. 10(11), pages 1-17, November.
    4. Aldrighetti, Riccardo & Battini, Daria & Ivanov, Dmitry & Zennaro, Ilenia, 2021. "Costs of resilience and disruptions in supply chain network design models: A review and future research directions," International Journal of Production Economics, Elsevier, vol. 235(C).

    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. Jiguang Wang & Yucai Wu, 2019. "A Continuous Approximation Approach Based on Regular Hexagon Partition for the Facility Location Problem under Disruptions Risk," Complexity, Hindawi, vol. 2019, pages 1-12, February.
    2. Aldrighetti, Riccardo & Battini, Daria & Ivanov, Dmitry & Zennaro, Ilenia, 2021. "Costs of resilience and disruptions in supply chain network design models: A review and future research directions," International Journal of Production Economics, Elsevier, vol. 235(C).
    3. Nader Azad & Elkafi Hassini, 2019. "A Benders Decomposition Method for Designing Reliable Supply Chain Networks Accounting for Multimitigation Strategies and Demand Losses," Transportation Science, INFORMS, vol. 53(5), pages 1287-1312, September.
    4. Azad, Nader & Hassini, Elkafi, 2019. "Recovery strategies from major supply disruptions in single and multiple sourcing networks," European Journal of Operational Research, Elsevier, vol. 275(2), pages 481-501.
    5. Ansari, Sina & Başdere, Mehmet & Li, Xiaopeng & Ouyang, Yanfeng & Smilowitz, Karen, 2018. "Advancements in continuous approximation models for logistics and transportation systems: 1996–2016," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 229-252.
    6. Cui, Jianxun & Zhao, Meng & Li, Xiaopeng & Parsafard, Mohsen & An, Shi, 2016. "Reliable design of an integrated supply chain with expedited shipments under disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 143-163.
    7. Zarrinpoor, Naeme & Fallahnezhad, Mohammad Saber & Pishvaee, Mir Saman, 2018. "The design of a reliable and robust hierarchical health service network using an accelerated Benders decomposition algorithm," European Journal of Operational Research, Elsevier, vol. 265(3), pages 1013-1032.
    8. An, Yu & Zeng, Bo & Zhang, Yu & Zhao, Long, 2014. "Reliable p-median facility location problem: two-stage robust models and algorithms," Transportation Research Part B: Methodological, Elsevier, vol. 64(C), pages 54-72.
    9. Cheng, Chun & Qi, Mingyao & Zhang, Ying & Rousseau, Louis-Martin, 2018. "A two-stage robust approach for the reliable logistics network design problem," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 185-202.
    10. Fan, Hongqiang & Yun, Lifen & Li, Xiaopeng, 2022. "A linear-time crystal-growth algorithm for discretization of continuum approximation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    11. Yu, Guodong & Zhang, Jie, 2018. "Multi-dual decomposition solution for risk-averse facility location problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 116(C), pages 70-89.
    12. Wang, Xin & Lim, Michael K. & Ouyang, Yanfeng, 2015. "Infrastructure deployment under uncertainties and competition: The biofuel industry case," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 1-15.
    13. Li, Xiaopeng, 2013. "An integrated modeling framework for design of logistics networks with expedited shipment services," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 56(C), pages 46-63.
    14. Yongzhen Li & Xueping Li & Jia Shu & Miao Song & Kaike Zhang, 2022. "A General Model and Efficient Algorithms for Reliable Facility Location Problem Under Uncertain Disruptions," INFORMS Journal on Computing, INFORMS, vol. 34(1), pages 407-426, January.
    15. Dmitry Ivanov & Alexandre Dolgui & Boris Sokolov & Marina Ivanova, 2017. "Literature review on disruption recovery in the supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 55(20), pages 6158-6174, October.
    16. Yu, Guodong & Haskell, William B. & Liu, Yang, 2017. "Resilient facility location against the risk of disruptions," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 82-105.
    17. Yun, Lifen & Fan, Hongqiang & Li, Xiaopeng, 2019. "Reliable facility location design with round-trip transportation under imperfect information part II: A continuous model," Transportation Research Part B: Methodological, Elsevier, vol. 124(C), pages 44-59.
    18. Zhang, Yanzi & Diabat, Ali & Zhang, Zhi-Hai, 2021. "Reliable closed-loop supply chain design problem under facility-type-dependent probabilistic disruptions," Transportation Research Part B: Methodological, Elsevier, vol. 146(C), pages 180-209.
    19. 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.
    20. Li, Xiaopeng & Ouyang, Yanfeng & Peng, Fan, 2013. "A supporting station model for reliable infrastructure location design under interdependent disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 60(C), pages 80-93.

    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:10:y:2018:i:9:p:3099-:d:166793. 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.