Journal of Humanitarian Logistics and Supply Chain Management (Dec 2017)

Decision support framework for location selection and disaster relief network design

  • Giuseppe Timperio,
  • Gajanan Bhanudas Panchal,
  • Avinash Samvedi,
  • Mark Goh,
  • Robert De Souza

DOI
https://doi.org/10.1108/JHLSCM-11-2016-0040
Journal volume & issue
Vol. 7, no. 3
pp. 222 – 245

Abstract

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Purpose – The purpose of this paper is to provide a decision support framework for locations identification to address network design in the domain of disaster relief supply chains. The solution approach is then applied to a real-life case about Indonesia. Design/methodology/approach – An approach integrating geographic information system technology and fuzzy analytical hierarchy process has been used. Findings – For the Indonesian case, distribution centers should be located in Pekanbaru, Surabaya, Banjarmasin, Ambon, Timika, and Manado. Research limitations/implications – The main limitation of this work is that facilities being sited are incapacitated. Inclusion of constraints over capacity would elevate the framework to a further level of sophistication, enabling virtual pool of inventory that can be used to adsorb fluctuation in the demand due to disasters. Practical implications – The use case provided in this paper shows a practical example of applicability for the proposed framework. This study is able to support worldwide decision makers facing challenges related with disaster relief chains resilience. In order to achieve efficiency and effectiveness in relief operations, strategic logistics planning in preparedness is key. Hence, initiatives in disaster preparedness should be enhanced. Originality/value – It adds value to the previous literature on humanitarian logistics by providing a real-life case study as use case for the proposed methodology. It can guide decision makers in designing resilient humanitarian response, worldwide. Moreover, a combination of recommendations from humanitarian logistics practitioners with established models in facility location sciences provides an interdisciplinary solution to this complex exercise.

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