IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i22p15900-d1279395.html
   My bibliography  Save this article

Designing the Distribution Network of Essential Items in the Critical Conditions of Earthquakes and COVID-19 Simultaneously

Author

Listed:
  • Sina Abbasi

    (Department of Industrial Engineering, Lahijan Branch, Islamic Azad University, Lahijan 1616, Iran)

  • Ilias Vlachos

    (Excelia Business School, Excelia Group, 17000 La Rochelle, France)

  • Shabnam Rekabi

    (School of Industrial & Systems Engineering, College of Engineering, University of Tehran, Tehran 141556311, Iran)

  • Mohammad Talooni

    (School of Industrial Engineering, College of Engineering, University of Tehran, Tehran 141556311, Iran)

Abstract

Current societies must make the necessary plans for effective responses and to reduce the destructive effects of disasters. For this reason, this research has developed a mathematical programming model under uncertainty for earthquake relief and response during COVID-19. In the presented model, the possibility of facility failure is considered according to the intensity of the earthquake and COVID-19 to increase reliability. The simultaneous occurrence of these disasters presents unique challenges in ensuring the timely delivery of essential supplies to affected regions. Distribution centers (DCs) are considered to be of two types: the first type is local DCs, which use public centers and are close to accident points. These types of centers are prone to failure because they use public facilities. Another type is the reliable DCs built outside the disrupted area, which have a very low probability of loss due to spending more money to build them. In addition, to consider the reliability capabilities, the new model has tried to provide a complete model for transportation planning by considering the multi-trip mode of vehicles. Moreover, this model considers distance restriction at the demand point for the first time because of COVID-19 during the earthquake. The proposed network design aims to offer effective solutions in promptly delivering essential items to affected areas, thereby enhancing disaster management strategies and minimizing the impact of these crises on vulnerable populations. Uncertainty is presented using the probability approach based on the modeling scenario and a case study from the city of Istanbul to illustrate the performance of the suggested model. Finally, the suggested mode is solved with an Lp-metric and goal programming (GP) approach. The results show that in this case, the proposed model shows that effective and efficient aid delivery is possible in terms of time and cost. Therefore, it can help crisis managers respond by providing the required budget and appropriate logistics planning.

Suggested Citation

  • Sina Abbasi & Ilias Vlachos & Shabnam Rekabi & Mohammad Talooni, 2023. "Designing the Distribution Network of Essential Items in the Critical Conditions of Earthquakes and COVID-19 Simultaneously," Sustainability, MDPI, vol. 15(22), pages 1-23, November.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:22:p:15900-:d:1279395
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/22/15900/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/22/15900/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ghasemi, Peiman & Khalili-Damghani, Kaveh & Hafezalkotob, Ashkan & Raissi, Sadigh, 2019. "Uncertain multi-objective multi-commodity multi-period multi-vehicle location-allocation model for earthquake evacuation planning," Applied Mathematics and Computation, Elsevier, vol. 350(C), pages 105-132.
    2. Hosseini-Motlagh, Seyyed-Mahdi & Samani, Mohammad Reza Ghatreh & Homaei, Shamim, 2023. "Design of control strategies to help prevent the spread of COVID-19 pandemic," European Journal of Operational Research, Elsevier, vol. 304(1), pages 219-238.
    3. Chang, Ching-Ter, 2000. "An efficient linearization approach for mixed-integer problems," European Journal of Operational Research, Elsevier, vol. 123(3), pages 652-659, June.
    4. Tofighi, S. & Torabi, S.A. & Mansouri, S.A., 2016. "Humanitarian logistics network design under mixed uncertainty," European Journal of Operational Research, Elsevier, vol. 250(1), pages 239-250.
    5. Cotes, Nathalie & Cantillo, Victor, 2019. "Including deprivation costs in facility location models for humanitarian relief logistics," Socio-Economic Planning Sciences, Elsevier, vol. 65(C), pages 89-100.
    6. Muhittin Oral & Ossama Kettani, 1992. "A Linearization Procedure for Quadratic and Cubic Mixed-Integer Problems," Operations Research, INFORMS, vol. 40(1-supplem), pages 109-116, February.
    7. A. Anaya-Arenas & J. Renaud & A. Ruiz, 2014. "Relief distribution networks: a systematic review," Annals of Operations Research, Springer, vol. 223(1), pages 53-79, December.
    8. Balcik, Burcu & Beamon, Benita M. & Krejci, Caroline C. & Muramatsu, Kyle M. & Ramirez, Magaly, 2010. "Coordination in humanitarian relief chains: Practices, challenges and opportunities," International Journal of Production Economics, Elsevier, vol. 126(1), pages 22-34, July.
    9. Alem, Douglas & Clark, Alistair & Moreno, Alfredo, 2016. "Stochastic network models for logistics planning in disaster relief," European Journal of Operational Research, Elsevier, vol. 255(1), pages 187-206.
    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. Renata Turkeš & Daniel Palhazi Cuervo & Kenneth Sörensen, 2019. "Pre-positioning of emergency supplies: does putting a price on human life help to save lives?," Annals of Operations Research, Springer, vol. 283(1), pages 865-895, December.
    2. Rodolfo Modrigais Strauss Nunes & Susana Carla Farias Pereira, 2022. "Intellectual structure and trends in the humanitarian operations field," Annals of Operations Research, Springer, vol. 319(1), pages 1099-1157, December.
    3. Hu, Shaolong & Han, Chuanfeng & Dong, Zhijie Sasha & Meng, Lingpeng, 2019. "A multi-stage stochastic programming model for relief distribution considering the state of road network," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 64-87.
    4. Abhishek Behl & Pankaj Dutta, 2019. "Humanitarian supply chain management: a thematic literature review and future directions of research," Annals of Operations Research, Springer, vol. 283(1), pages 1001-1044, December.
    5. Sabbaghtorkan, Monir & Batta, Rajan & He, Qing, 2020. "Prepositioning of assets and supplies in disaster operations management: Review and research gap identification," European Journal of Operational Research, Elsevier, vol. 284(1), pages 1-19.
    6. Sun, Huali & Li, Jiamei & Wang, Tingsong & Xue, Yaofeng, 2022. "A novel scenario-based robust bi-objective optimization model for humanitarian logistics network under risk of disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    7. Hasti Seraji & Reza Tavakkoli-Moghaddam & Sobhan Asian & Harpreet Kaur, 2022. "An integrative location-allocation model for humanitarian logistics with distributive injustice and dissatisfaction under uncertainty," Annals of Operations Research, Springer, vol. 319(1), pages 211-257, December.
    8. Alegoz, Mehmet & Acar, Muge & Salman, F. Sibel, 2024. "Value of sorting and recovery in post-disaster relief aid distribution," Omega, Elsevier, vol. 122(C).
    9. Rodríguez-Espíndola, Oscar & Albores, Pavel & Brewster, Christopher, 2018. "Disaster preparedness in humanitarian logistics: A collaborative approach for resource management in floods," European Journal of Operational Research, Elsevier, vol. 264(3), pages 978-993.
    10. 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).
    11. 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.
    12. Konstantinos Nikolopoulos & Fotios Petropoulos & Vasco Sanchez Rodrigues & Stephen Pettit & Anthony Beresford, 2019. "A risk-mitigation model driven from the level of forecastability of Black Swans: prepare and respond to major Earthquakes through a dynamic Temporal and Spatial Aggregation forecasting framework," Working Papers 19017, Bangor Business School, Prifysgol Bangor University (Cymru / Wales).
    13. Nikolopoulos, Konstantinos & Petropoulos, Fotios & Rodrigues, Vasco Sanchez & Pettit, Stephen & Beresford, Anthony, 2022. "A disaster response model driven by spatial–temporal forecasts," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1214-1220.
    14. Zhang, Lingye & Lu, Jing & Yang, Zaili, 2021. "Optimal scheduling of emergency resources for major maritime oil spills considering time-varying demand and transportation networks," European Journal of Operational Research, Elsevier, vol. 293(2), pages 529-546.
    15. Chen, Yingzhen & Zhao, Qiuhong & Huang, Kai & Xi, Xunzhuo, 2022. "A Bi-objective optimization model for contract design of humanitarian relief goods procurement considering extreme disasters," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    16. Afshin Kamyabniya & M. M. Lotfi & Mohsen Naderpour & Yuehwern Yih, 2018. "Robust Platelet Logistics Planning in Disaster Relief Operations Under Uncertainty: a Coordinated Approach," Information Systems Frontiers, Springer, vol. 20(4), pages 759-782, August.
    17. Laura Laguna-Salvadó & Matthieu Lauras & Uche Okongwu & Tina Comes, 2019. "A multicriteria Master Planning DSS for a sustainable humanitarian supply chain," Annals of Operations Research, Springer, vol. 283(1), pages 1303-1343, December.
    18. Doan, Xuan Vinh & Shaw, Duncan, 2019. "Resource allocation when planning for simultaneous disasters," European Journal of Operational Research, Elsevier, vol. 274(2), pages 687-709.
    19. Peiyu Zhang & Yankui Liu & Guoqing Yang & Guoqing Zhang, 2022. "A multi-objective distributionally robust model for sustainable last mile relief network design problem," Annals of Operations Research, Springer, vol. 309(2), pages 689-730, February.
    20. Dukkanci, Okan & Koberstein, Achim & Kara, Bahar Y., 2023. "Drones for relief logistics under uncertainty after an earthquake," European Journal of Operational Research, Elsevier, vol. 310(1), pages 117-132.

    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:15:y:2023:i:22:p:15900-:d:1279395. 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.