Multi-level facility location-allocation problem for post-disaster humanitarian relief distribution: A case study

Seyed Mahdi Shavarani

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Abstract

Purpose
Previously use of drones as a relief distribution vehicle was studied in several studies where required number of drones and the best locations for the relief centers were investigated. The maximum travel distance of drones without a need to recharge is limited by their endurance. Recharge stations can be used to extend the coverage area of the drones. The purpose of this paper is to find the best topology for both relief centers and recharge stations to cover a large-scale area with minimum and feasible incurred costs and waiting times.

Design/methodology/approach
A multi-level facility location problem (FLP) is utilized to find the optimum number of relief centers and refuel stations and their locations. It is supposed that the demand occurs according to Poisson distribution. The allocation of the demand is based on nearest neighborhood method. A hybrid genetic algorithm is proposed to solve the model. The performance of the algorithm is examined through a case study.

Findings
The proposed method delivers increased efficiency and responsiveness of the humanitarian relief system. The coverage area of the drones is extended by refuel stations, total costs of the system are reduced and the time to respond an emergency, which is an important factor in survival rate, is significantly decreased.

Originality/value
This study proposes a multi-level FLP to simultaneously account for recharge stations, relief centers and the number of required drones to cover all the demand for relief in a post-disaster period.
Original languageEnglish
Pages (from-to)70-81
Number of pages12
JournalJournal of Humanitarian Logistics and Supply Chain Management
Volume9
Issue number1
Early online date9 Apr 2019
DOIs
Publication statusPublished - 30 Apr 2019

Keywords

  • Drone
  • Multi-level FLP
  • Post-disaster humanitarian relief
  • Supply chain management in disaster relief
  • UAV

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