Paper Info
Title
Prepositioning Emergency Supplies To Support Disaster Relief: A Case Study Using Stochastic Programming
Abstract
This paper studies the strategic problem of designing emergency supply networks to support disaster relief over a planning horizon. The problem addresses decisions on the location and number of distribution centres needed, their capacity, and the quantity of each emergency item to keep in stock. It builds on a case study inspired by real-world data obtained from the North Carolina Emergency Management Division (NCEM) and the Federal Emergency Management Agency (FEMA). To tackle the problem, a scenariobased approach is proposed involving three phases: disaster scenario generation, design generation and design evaluation. Disasters are modelled as stochastic processes and a Monte Carlo procedure is derived to generate plausible catastrophic scenarios. Based on this detailed representation of disasters, a multi-phase modelling framework is proposed to design the emergency supply network. The two-stage stochastic programming model proposed is solved using a sample average approximation method. This scenario-based solution approach is applied to the case study to generate plausible scenarios, to produce alternative designs and to evaluate them on a set of performance measures in order to select the best design.
Year
DOI
Venue
2018
10.1080/03155986.2017.1335045
INFOR
Keywords
DocType
Volume
Humanitarian logistics, relief network design, risk modelling, multi-hazards, stochastic programming, Monte Carlo scenarios
Journal
56
Issue
ISSN
Citations 
1
0315-5986
0
PageRank 
References 
Authors
0.34
19
3
Name
Order
Citations
PageRank
Walid Klibi11949.89
Soumia Ichoua229918.21
Alain Martel300.34