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G-network Models to Support Planning for Disaster Relief Distribution

Merve Ozen and Ananth Krishnamurthy
Journal Name
International Journal of Production Research
Journal Publication
others
Publication Year
2022
Journal Publications Functional Area
Decision Sciences
Publication Date
Vol. 60(5), 2022, Pg. 1621-1632
Abstract

One of the key activities during disaster response is distributing relief items to victims. This is a challenging task due to dynamically changing victim needs and disaster aftermath conditions. We model the distribution operations where items like tarpaulins and blankets are distributed by volunteers, to victims at temporary distribution areas called relief centers (RC). We investigate the impact victim movements have on the distribution performance. We model each RC as a queue, and the distribution operation as a generalised queuing network (G-network). We investigate product form solutions for the proposed G-network model, and prove a new product form result for G-networks with signals and batch transfer under certain conditions. We leverage this result to develop product form approximations that apply across a broad range of settings. We apply the G-network model to a case study using the Nepal earthquake relief distribution data, and quantify the impact of victim movement on network performance.

G-network Models to Support Planning for Disaster Relief Distribution

Author(s) Name: Merve Ozen and Ananth Krishnamurthy
Journal Name: International Journal of Production Research
Volume: Vol. 60(5), 2022, Pg. 1621-1632
Year of Publication: 2022
Abstract:

One of the key activities during disaster response is distributing relief items to victims. This is a challenging task due to dynamically changing victim needs and disaster aftermath conditions. We model the distribution operations where items like tarpaulins and blankets are distributed by volunteers, to victims at temporary distribution areas called relief centers (RC). We investigate the impact victim movements have on the distribution performance. We model each RC as a queue, and the distribution operation as a generalised queuing network (G-network). We investigate product form solutions for the proposed G-network model, and prove a new product form result for G-networks with signals and batch transfer under certain conditions. We leverage this result to develop product form approximations that apply across a broad range of settings. We apply the G-network model to a case study using the Nepal earthquake relief distribution data, and quantify the impact of victim movement on network performance.