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A stochastic bi-objective simulation–optimization model for cascade disaster location-allocation-distribution problems

Author

Listed:
  • Kaveh Khalili-Damghani

    (South-Tehran Branch, Islamic Azad University)

  • Madjid Tavana

    (La Salle University
    University of Paderborn)

  • Peiman Ghasemi

    (Islamic Azad University)

Abstract

Cascade disasters can destroy urban infrastructures, kill thousands of people, and permanently displace millions of people. The paramount goal of disaster relief programs is to save lives, reduce financial loss, and accelerate the relief process. This study proposes a bi-level two-echelon mathematical model to minimize pre-disaster costs and maximize post-disaster relief coverage area. The model uses a geographic information system (GIS) to classify the disaster area and determine the optimal number and location of distribution centers while minimizing the relief supplies’ inventory costs. A simulation model is used to estimate the demand for relief supplies. Initially, vulnerable urban infrastructures are identified, and then the interaction among them is investigated for cascade disasters. The aims of this study are threefold: (1) to identify vulnerable urban infrastructures in cascade disasters, (2) to prioritize urban areas based on the severity of cascade disasters using a GIS, and (3) to develop a bi-objective multi-echelon multi-supplies mathematical model for location, allocation, and distribution of relief supplies under uncertainty. The model is solved with an epsilon-constraint method for small and medium-scale problems and the invasive weed optimization algorithm for large-scale problems. A case study is presented to demonstrate the applicability and efficacy of the proposed method. The results confirm the difficulty of relief operations during the night as the cost of night-time relief operations is higher than daytime. In addition, the results show the coverage area increases as the demand surges. Therefore, establishing more distribution centers will increase operating costs and expand coverage are.

Suggested Citation

  • Kaveh Khalili-Damghani & Madjid Tavana & Peiman Ghasemi, 2022. "A stochastic bi-objective simulation–optimization model for cascade disaster location-allocation-distribution problems," Annals of Operations Research, Springer, vol. 309(1), pages 103-141, February.
    • Handle: RePEc:spr:annopr:v:309:y:2022:i:1:d:10.1007_s10479-021-04191-0
    DOI: 10.1007/s10479-021-04191-0
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    References listed on IDEAS

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    Cited by:

    1. Gang Wang, 2024. "Disaster relief supply chain network planning under uncertainty," Annals of Operations Research, Springer, vol. 338(2), pages 1127-1156, July.
    2. Afshin Kamyabniya & Antoine Sauré & F. Sibel Salman & Noureddine Bénichou & Jonathan Patrick, 2024. "Optimization models for disaster response operations: a literature review," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 46(3), pages 737-783, September.
    3. Shaoren Wang & Yenchun Jim Wu & Ruiting Li, 2022. "An Improved Genetic Algorithm for Location Allocation Problem with Grey Theory in Public Health Emergencies," IJERPH, MDPI, vol. 19(15), pages 1-18, August.

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