A multiagent approach to solving the dynamic postdisaster relief distribution problem

Julián Alberto Espejo-Díaz () and William J. Guerrero ()
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Julián Alberto Espejo-Díaz: Universidad de La Sabana
William J. Guerrero: Universidad de La Sabana

Operations Management Research, 2021, vol. 14, issue 1, No 12, 177-193

Abstract: Abstract In the immediate aftermath of any disaster event, operational decisions are made to relieve the affected population and minimize casualties and human suffering. One of the most crucial decisions concerns the delivery of the correct amount of humanitarian aid at the right moment to the right place. This decision should be made considering the dynamism of disaster response operations where information is unknown beforehand and varies over time. For instance, victims’ word of mouth and impatience when facing shortages can make them decide to leave distribution points (DPs), impacting relief distribution operations. Therefore, inventory and transportation decisions should be made continuously to better serve affected people. This work presents a simulation-optimization approach to dynamically studying disaster relief inventory and routing decisions. An agent-based simulation model recreates humanitarian aid distribution operations, including behavioral factors such as victims’ word of mouth and impatience. Additionally, inventory routing schemes are created using a mathematical model. A case study motivated by the 2017 Mocoa landslide in Colombia is developed and presented for use in conjunction with the proposed framework. The key findings of the study reveal the importance of considering changes in demand at DPs that can be caused by victims’ word of mouth and impatience when planning disaster relief distribution operations. Including such factors and making inventory and transportation decisions frequently will improve the service level indicators in humanitarian response operations.

Keywords: Humanitarian logistics; Simulation-based optimization; Word of mouth; Inventory routing problem (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s12063-021-00192-1

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