Humanitarian Logistics: a Clustering Methodology for Assisting Humanitarian Operations

Authors

  • Fabiana santos Lima Federal University of Santa Catarina
  • Daniel de Oliveira Federal University of Santa Catarina
  • Mirian Buss Gonçalves Federal University of Santa Catarina
  • Márcia Marcondes Altimari Samed State University of Maringá, Brazil

DOI:

https://doi.org/10.4067/S0718-27242014000200007

Keywords:

Humanitarian Logistics, Clusters, Natural Disasters, Preparedness and Response, Procurement of Relief Supplies

Abstract

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).

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Author Biographies

Fabiana santos Lima, Federal University of Santa Catarina

Programa de Pós-Graduação em Engenharia de Produção.

Daniel de Oliveira, Federal University of Santa Catarina

Programa de Pós-Graduação em Engenharia de Produção.

Mirian Buss Gonçalves, Federal University of Santa Catarina

Programa de Pós-Graduação em Engenharia de Produção.

Márcia Marcondes Altimari Samed, State University of Maringá, Brazil

Departamento de Engenharia de Produção.

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Published

2014-06-19

How to Cite

Lima, F. santos, Oliveira, D. de, Gonçalves, M. B., & Samed, M. M. A. (2014). Humanitarian Logistics: a Clustering Methodology for Assisting Humanitarian Operations. Journal of Technology Management & Innovation, 9(2), 86–97. https://doi.org/10.4067/S0718-27242014000200007

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Section

Research Articles