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Resource allocation models for material convergence

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  • Ozen, Merve
  • Krishnamurthy, Ananth

Abstract

Immediately after a major disaster large volumes of solicited and unsolicited relief items start to flow into the disaster affected region. This phenomenon is known as material convergence. The sheer volume of incoming materials, coupled with limited resources, make sorting and distribution of relief items a difficult task. The challenge is exacerbated when a large portion of the unsolicited donations are low-priority or inappropriate items, diverting volunteer, space, and transportation capacity from more critical items. This paper investigates volunteer allocation decisions under material convergence and varying levels of high-priority donations. First, we interview disaster response practitioners to understand challenges with resource allocation decisions. Then, we model the donation arrival and sorting process for both solicited and unsolicited donations as transient multi-server queues. Using this model, we quantify the level of material convergence and evaluate the impact of resource allocation decisions on relief item output. We provide insights that can help address the problems of resource allocation under material convergence, that are critical to satisfy needs of disaster victims.

Suggested Citation

  • Ozen, Merve & Krishnamurthy, Ananth, 2020. "Resource allocation models for material convergence," International Journal of Production Economics, Elsevier, vol. 228(C).
    • Handle: RePEc:eee:proeco:v:228:y:2020:i:c:s0925527320300463
    DOI: 10.1016/j.ijpe.2020.107646
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    References listed on IDEAS

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    1. Rodríguez-Espíndola, Oscar & Albores, Pavel & Brewster, Christopher, 2018. "Dynamic formulation for humanitarian response operations incorporating multiple organisations," International Journal of Production Economics, Elsevier, vol. 204(C), pages 83-98.
    2. Caunhye, Aakil M. & Nie, Xiaofeng & Pokharel, Shaligram, 2012. "Optimization models in emergency logistics: A literature review," Socio-Economic Planning Sciences, Elsevier, vol. 46(1), pages 4-13.
    3. M. Ülkü & Kathryn Bell & Stephanie Wilson, 2015. "Modeling the impact of donor behavior on humanitarian aid operations," Annals of Operations Research, Springer, vol. 230(1), pages 153-168, July.
    4. Donald Gross & Douglas R. Miller, 1984. "The Randomization Technique as a Modeling Tool and Solution Procedure for Transient Markov Processes," Operations Research, INFORMS, vol. 32(2), pages 343-361, April.
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    Cited by:

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    2. Li, Linda & Firouz, Mohammad & Ahmed, Abdulaziz & Delen, Dursun, 2023. "On the Egalitarian–Utilitarian spectrum in stochastic capacitated resource allocation problems," International Journal of Production Economics, Elsevier, vol. 262(C).
    3. Rodríguez-Espíndola, Oscar & Ahmadi, Hossein & Gastélum-Chavira, Diego & Ahumada-Valenzuela, Omar & Chowdhury, Soumyadeb & Dey, Prasanta Kumar & Albores, Pavel, 2023. "Humanitarian logistics optimization models: An investigation of decision-maker involvement and directions to promote implementation," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    4. Alegoz, Mehmet & Acar, Muge & Salman, F. Sibel, 2024. "Value of sorting and recovery in post-disaster relief aid distribution," Omega, Elsevier, vol. 122(C).

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