Humanitarian Logistics: a Clustering Methodology for Assisting Humanitarian Operations
Lima, Fabiana santos
Oliveira, Daniel de
Gonçalves, Mirian Buss
Samed, Márcia Marcondes Altimari
In this paper, we propose a methodology to identify and classify regions by the type and frequency of disasters. The data on the clusters allow you to extract information that can be used in the preparedness phase as well as to identify the relief items needed to meet each cluster. Using this approach, the clusters are formed by using a computing tool that uses as the input the history data of the disasters in the Brazilian state of Santa Catarina, with a specific focus on: windstorms, hail, floods, droughts, landslides, and flash floods. The results show that the knowledge provided by the clustering analysis contributes to the decision making process in the response phase of Humanitarian Logistics (HL).