Luego de 3 años les presento mi libro, escrito en francés; Conception des Chaînes Logistiques Humanitaires Efficientes et Résilientes. Application au cas de Crises Récurrentes Péruviennes, Presses Académiques Francophones, ISBN 978-3-8381-4934-9, 244 paginas, Saarbrücken: Alemania.
Every year, more than 400 natural disasters hit the world. To assist those affected populations, humanitarian organizations store in advance emergency aid in warehouses. This book provides tools for support decisions on localization and sizing of humanitarian warehouses. Our approach is based on the design of representative and realistic scenarios. A scenario expresses some disasters’ occurrences for which epicenters are known, as well as their gravity and frequency. This step is based on the exploitation and analysis of databases of past disasters. The second step tackles about possible disaster’s propagation. The objective consists in determining their impact on population on each affected area. This impact depends on vulnerability and resilience of the territory. Vulnerability measures expected damage values meanwhile resilience estimates the ability to withstand some shock and recover quickly. Both are largely determined by social and economic factors, being structural (geography, GDP, etc.) or political (establishment or not relief infrastructure, presence and strict enforcement of construction standards, etc.). We propose through Principal Component Analysis (PCA) to identify, for each territory, influential factors of resilience and vulnerability and then estimate the number of victims concerned using these factors. Often, infrastructure (water, telecommunications, electricity, communication channels) are destroyed or damaged by the disaster (e.g. Haiti in 2010). The last step aims to assess the disaster logistics impact, specifically those related to with: transportation flows capacity limitations and destruction of all or part of emergency relief inventories. The following of our study focuses on location and allocation of a warehouses’ network. The proposed models have the originality to consider potential resources and infrastructure degradation after a disaster (resilience dimension) and seek optimizing the equilibrium between costs and results (effectiveness dimension). Initially we consider a single scenario. The problem is an extension of classical location studies. Then we consider a set of probable scenarios. This approach is essential due to the highly uncertain character of humanitarian disasters. All of these contributions have been tested and validated through a real application case: Peruvian recurrent disasters. These crises, mainly due to earthquakes and floods (El Niño), require establishment of a first aid logistics network that should be resilient and efficient.