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Earthquake Decision-Making Tool for Humanitarian Logistics Network: An Application in Popayan, Colombia

Author

Listed:
  • Helmer Paz-Orozco

    (Facultad de Ingeniería, Corporación Universitaria Comfacauca-Unicomfacauca, Popayán 190001, Colombia)

  • Irineu de Brito Junior

    (Environmental Engineering Department, São Paulo State University, São José dos Campos 12247-004, Brazil)

  • Mario Chong

    (School of Business Engineering, Universidad del Pacifico, Lima 15072, Peru)

  • Yesid Anacona-Mopan

    (Facultad de Ingeniería, Corporación Universitaria Comfacauca-Unicomfacauca, Popayán 190001, Colombia)

  • Jhon Alexander Segura Dorado

    (Facultad de Ingeniería, Corporación Universitaria Comfacauca-Unicomfacauca, Popayán 190001, Colombia)

  • Mariana Moyano

    (School of Business Engineering, Universidad del Pacifico, Lima 15072, Peru)

Abstract

Background : This study presents a comprehensive methodology for enhancing humanitarian logistics planning and management in natural disasters, focusing on earthquakes. Methods : The innovative approach combines a deterministic mathematical model with a simulation model to address the problem from multiple perspectives, aiming to improve efficiency and equity in post-disaster supply distribution. In the deterministic modeling phase, optimal locations for humanitarian distribution centers and points in Popayan, Colombia, were identified, enabling efficient resource allocation for affected families. Subsequently, the simulation model evaluated scenarios based on real earthquakes in Colombia and Latin America, providing a comprehensive view of the logistics system’s response capacity to different disaster conditions and magnitudes. Results : The results demonstrated that the proposed methodology significantly reduced supply delivery time, achieving a 30% improvement compared to traditional humanitarian logistics approaches. Moreover, it led to a more equitable coverage of affected communities, with a 25% increase in families served in previously underserved areas. Expert validation from the Disaster Risk Management Committee of the study area confirmed the methodology’s usefulness for informed and effective decision-making in real situations. Conclusions: This integrated approach of mathematical modeling and discrete event simulation offers valuable insights to address disaster management and support decision-making in humanitarian crises.

Suggested Citation

  • Helmer Paz-Orozco & Irineu de Brito Junior & Mario Chong & Yesid Anacona-Mopan & Jhon Alexander Segura Dorado & Mariana Moyano, 2023. "Earthquake Decision-Making Tool for Humanitarian Logistics Network: An Application in Popayan, Colombia," Logistics, MDPI, vol. 7(4), pages 1-18, October.
    • Handle: RePEc:gam:jlogis:v:7:y:2023:i:4:p:68-:d:1252574
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    References listed on IDEAS

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    1. Esposito Amideo, A. & Scaparra, M.P. & Kotiadis, K., 2019. "Optimising shelter location and evacuation routing operations: The critical issues," European Journal of Operational Research, Elsevier, vol. 279(2), pages 279-295.
    2. Xuehong Gao, 2022. "A bi-level stochastic optimization model for multi-commodity rebalancing under uncertainty in disaster response," Annals of Operations Research, Springer, vol. 319(1), pages 115-148, December.
    3. L N Van Wassenhove, 2006. "Humanitarian aid logistics: supply chain management in high gear," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(5), pages 475-489, May.
    4. Ghasemi, Peiman & Khalili-Damghani, Kaveh, 2021. "A robust simulation-optimization approach for pre-disaster multi-period location–allocation–inventory planning," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 179(C), pages 69-95.
    5. Shalini Kurapati & Ioanna Kourounioti & Heide Lukosch & Lóránt Tavasszy & Alexander Verbraeck, 2018. "Fostering Sustainable Transportation Operations through Corridor Management: A Simulation Gaming Approach," Sustainability, MDPI, vol. 10(2), pages 1-18, February.
    6. Shahparvari, Shahrooz & Abbasi, Babak, 2017. "Robust stochastic vehicle routing and scheduling for bushfire emergency evacuation: An Australian case study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 104(C), pages 32-49.
    7. Andrés Felipe Solis Pino & Ginna Andrea Ramirez Palechor & Yesid Ediver Anacona Mopan & Victoria E. Patiño-Arenas & Pablo H. Ruiz & Vanessa Agredo-Delgado & Alicia Mon, 2022. "Determination of Population Mobility Dynamics in Popayán-Colombia during the COVID-19 Pandemic Using Open Datasets," IJERPH, MDPI, vol. 19(22), pages 1-16, November.
    8. Ju Myung Song & Weiwei Chen & Lei Lei, 2018. "Supply chain flexibility and operations optimisation under demand uncertainty: a case in disaster relief," International Journal of Production Research, Taylor & Francis Journals, vol. 56(10), pages 3699-3713, May.
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