TY - JOUR
T1 - A location-allocation model for more consistent humanitarian supply chains
AU - Lauras, Matthieu
AU - Vargas, Jorge
AU - Dupont, Lionel
AU - Charles, Aurelie
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2014.
PY - 2014
Y1 - 2014
N2 - During the preparedness phase, humanitarians plan their relief response by studying the potential disasters, their consequences and the existing infrastructures and available resources. However, when the disaster occurs, some hazards can impact strongly the network by destroying some resources or collapsing infrastructures. Consequently, the performance of the relief network could be strongly decreased. The problem statement of our research work can be defined as the capability to design a consistent network that would be able to manage adequately the disaster response despite of potential failures or deficiencies of infrastructures and resources. Basically, our research work consists in proposing an innovative location-allocation model in order to improve the humanitarian response efficiency (cost minimization) and effectiveness (non-served beneficiaries minimization) regarding the foreseeable network weaknesses. A Stochastic Mixed Integer Program is proposed to reach this goal. A numerical application regarding the management of the Peruvian earthquake’s relief network is proposed to illustrate the benefits of our proposition.
AB - During the preparedness phase, humanitarians plan their relief response by studying the potential disasters, their consequences and the existing infrastructures and available resources. However, when the disaster occurs, some hazards can impact strongly the network by destroying some resources or collapsing infrastructures. Consequently, the performance of the relief network could be strongly decreased. The problem statement of our research work can be defined as the capability to design a consistent network that would be able to manage adequately the disaster response despite of potential failures or deficiencies of infrastructures and resources. Basically, our research work consists in proposing an innovative location-allocation model in order to improve the humanitarian response efficiency (cost minimization) and effectiveness (non-served beneficiaries minimization) regarding the foreseeable network weaknesses. A Stochastic Mixed Integer Program is proposed to reach this goal. A numerical application regarding the management of the Peruvian earthquake’s relief network is proposed to illustrate the benefits of our proposition.
KW - Consistency
KW - Design scenarios
KW - Humanitarian supply chain
KW - Location-allocation
KW - Stochastic programming
UR - http://www.scopus.com/inward/record.url?scp=84922010258&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-11818-5_1
DO - 10.1007/978-3-319-11818-5_1
M3 - Article
AN - SCOPUS:84922010258
SN - 1865-1348
VL - 196
SP - 1
EP - 12
JO - Lecture Notes in Business Information Processing
JF - Lecture Notes in Business Information Processing
ER -