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Evaluating relief center designs for disaster relief distribution

Evaluating relief center designs for disaster relief distribution Relief item distribution to victims is a key activity during disaster response. Currently many humanitarian organizations follow simple guidelines based on experience to assess need and distribute relief supplies. However, the interviews with practitioners suggest a problem in efficiency in relief distribution efforts. The purpose of this paper is to develop a model and solution methodology that can estimate relief center (RC) performance, measured by waiting time for victims and throughput, for any RC design and analyze the impact of key design decisions on these performance measures.Design/methodology/approachInterviews with practitioners and current practice guidelines are used to understand relief distribution and a queuing network model is used to represent the relief distribution. Finally, the model is applied to data from the 2015 Nepal earthquake.FindingsThe findings identify that dissipating congestion created by crowds, varying item assignment decisions to points of distribution, limiting the physical RC capacity to control congestion and using triage queue to balance distribution times, are effective strategies that can improve RC performance.Research limitations/implicationsThis research bases the RC designs on Federal Emergency Management Agency guidelines and assumes a certain area and volunteer availability.Originality/valueThis paper contributes to humanitarian logistics by discussing useful insights that can impact how relief agencies set up and operate RCs. It also contributes to the queuing literature by deriving analytic solutions for the steady state probabilities of finite capacity, state dependent queues with blocking. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Humanitarian Logistics and Supply Chain Management Emerald Publishing

Evaluating relief center designs for disaster relief distribution

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References (56)

Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
2042-6747
DOI
10.1108/jhlscm-03-2017-0012
Publisher site
See Article on Publisher Site

Abstract

Relief item distribution to victims is a key activity during disaster response. Currently many humanitarian organizations follow simple guidelines based on experience to assess need and distribute relief supplies. However, the interviews with practitioners suggest a problem in efficiency in relief distribution efforts. The purpose of this paper is to develop a model and solution methodology that can estimate relief center (RC) performance, measured by waiting time for victims and throughput, for any RC design and analyze the impact of key design decisions on these performance measures.Design/methodology/approachInterviews with practitioners and current practice guidelines are used to understand relief distribution and a queuing network model is used to represent the relief distribution. Finally, the model is applied to data from the 2015 Nepal earthquake.FindingsThe findings identify that dissipating congestion created by crowds, varying item assignment decisions to points of distribution, limiting the physical RC capacity to control congestion and using triage queue to balance distribution times, are effective strategies that can improve RC performance.Research limitations/implicationsThis research bases the RC designs on Federal Emergency Management Agency guidelines and assumes a certain area and volunteer availability.Originality/valueThis paper contributes to humanitarian logistics by discussing useful insights that can impact how relief agencies set up and operate RCs. It also contributes to the queuing literature by deriving analytic solutions for the steady state probabilities of finite capacity, state dependent queues with blocking.

Journal

Journal of Humanitarian Logistics and Supply Chain Management – Emerald Publishing

Published: Mar 23, 2018

Keywords: Distribution; Disaster relief operations; Disaster aid; Blocking; Nepal earthquake; Queuing network

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