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Strategic emergency preparedness network design integrating supply and demand sides in a multi-objective approach

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  • Halit Üster
  • Jyotirmoy Dalal

Abstract

We consider integration of fast evacuation and cost-effective relief distribution objectives, the two critical aspects of emergency management, to design a strategic emergency preparedness network for foreseen disasters, such as hurricanes. To this end, we introduce the design of a three-tier system, involving evacuation source, shelters, and distribution centers, that integrates the relief (supply) and evacuation (demand) sides of an emergency preparedness network. This is motivated by the realization that the shelters are shared facilities at the interface of the supply and demand sides. Although primarily intended for strategic decision making, our model can also make tactical decisions, thus spanning two separate time frames before a disaster’s occurrence. To solve models for large-scale instances, we adopt a Benders Decomposition approach with an implementation that solves only one instance of the master problem. We also determine that, in this framework, tuning of master tree search parameters along with the strengthening of Benders cuts significantly impact convergence. We conduct an extensive computational study to examine the impact of algorithmic improvements and further consider a realistic case study based on geographic information system (GIS) data from coastal Texas and examine the effects of changing problem parameters. By comparing our approach with current practice, we illustrate that a pro-active strategic integration of evacuation and distribution can relieve the resource-constrained large urban areas, traditionally considered as shelter locations.

Suggested Citation

  • Halit Üster & Jyotirmoy Dalal, 2017. "Strategic emergency preparedness network design integrating supply and demand sides in a multi-objective approach," IISE Transactions, Taylor & Francis Journals, vol. 49(4), pages 395-413, April.
  • Handle: RePEc:taf:uiiexx:v:49:y:2017:i:4:p:395-413
    DOI: 10.1080/0740817X.2016.1234731
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    Citations

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    Cited by:

    1. Jyotirmoy Dalal & Halit Üster, 2021. "Robust Emergency Relief Supply Planning for Foreseen Disasters Under Evacuation-Side Uncertainty," Transportation Science, INFORMS, vol. 55(3), pages 791-813, May.
    2. Liu, Kanglin & Yang, Liu & Zhao, Yejia & Zhang, Zhi-Hai, 2023. "Multi-period stochastic programming for relief delivery considering evolving transportation network and temporary facility relocation/closure," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 180(C).
    3. Li, Yuchen & Zhang, Jianghua & Yu, Guodong, 2020. "A scenario-based hybrid robust and stochastic approach for joint planning of relief logistics and casualty distribution considering secondary disasters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    4. Jyotirmoy Dalal & Halit Üster, 2018. "Combining Worst Case and Average Case Considerations in an Integrated Emergency Response Network Design Problem," Transportation Science, INFORMS, vol. 52(1), pages 171-188, January.
    5. 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).
    6. Camur, Mustafa C. & Sharkey, Thomas C. & Dorsey, Clare & Grabowski, Martha R. & Wallace, William A., 2021. "Optimizing the response for Arctic mass rescue events," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    7. Bian Liang & Dapeng Yang & Xinghong Qin & Teresa Tinta, 2019. "A Risk-Averse Shelter Location and Evacuation Routing Assignment Problem in an Uncertain Environment," IJERPH, MDPI, vol. 16(20), pages 1-28, October.
    8. Yang, Hengfei & Yang, Yuze & Wang, Dujuan & Cheng, T.C.E. & Yin, Yunqiang & Hu, Hai, 2024. "A scenario-based robust approach for joint planning of multi-blood product logistics and multi-casualty type evacuation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 184(C).

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