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

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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.

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Acknowledgements

Dr. Madjid Tavana is grateful for the partial support he received from the Czech Science Foundation (GAˇCR19-13946S) for this research.

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Authors and Affiliations

  1. Department of Industrial Engineering, South-Tehran Branch, Islamic Azad University, Tehran, Iran

    Kaveh Khalili-Damghani

  2. Business Systems and Analytics Department, Distinguished Chair of Business Analytics, La Salle University, Philadelphia, PA, 19141, USA

    Madjid Tavana

  3. Business Information Systems Department, Faculty of Business Administration and Economics, University of Paderborn, 33098, Paderborn, Germany

    Madjid Tavana

  4. Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran

    Peiman Ghasemi

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  1. Kaveh Khalili-Damghani
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Correspondence to Madjid Tavana.

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Khalili-Damghani, K., Tavana, M. & Ghasemi, P. A stochastic bi-objective simulation–optimization model for cascade disaster location-allocation-distribution problems. Ann Oper Res 309, 103–141 (2022). https://doi.org/10.1007/s10479-021-04191-0

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