EURO-Online login
- New to EURO? Create an account
- I forgot my username and/or my password.
- Help with cookies
(important for IE8 users)
2125. Forecast-driven collaborative repositioning optimization. An application to Madagascar
Invited abstract in session TB-21: Demand Forecasting in Humanitarian Operations, stream OR in Humanitarian Operations (HOpe).
Tuesday, 10:30-12:00Room: 49 (building: 116)
Authors (first author is the speaker)
1. | Birce Adsanver
|
Logistics and Operations Management, HEC Montréal | |
2. | Burcu Balcik
|
Ozyegin University | |
3. | Valérie Bélanger
|
Logistics and Operations management, HEC Montréal | |
4. | Marie-Ève Rancourt
|
HEC Montreal |
Abstract
Disasters are increasingly affecting human lives with greater frequency and severity over the years. Depending on the forecasting capabilities, it is possible to anticipate and mitigate the impacts of certain events. Anticipatory actions, also known as forecast-based early actions, play a crucial role in this regard by allowing humanitarian actors to take proactive measures before the disasters strike. This study focuses on a repositioning problem in anticipation of storms within a collaborative countrywide network. The network involves multiple humanitarian agencies that strategically preposition relief supplies across different regions. When a storm is anticipated to hit the country, the agencies begin receiving forecast updates providing predictions on storm conditions. They estimate disaster impacts by utilizing the available forecasts and relocate the prepositioned supplies to the potentially affected regions for a faster response. We address this problem by proposing an analytical approach that provides relocation recommendations based on the forecasts. We collaborate with the Emergency Supply Prepositioning Group to design and integrate such a decision support tool into their “STOCKHOLM” platform, which offers prepositioned stock mapping and analyses to the stockholders. We test our approach and analyze the benefits of collaboration with a case study on Madagascar. The analyses are conducted by processing data related to the logistics network and storm forecasts.
Keywords
- Humanitarian Applications
- Supply Chain Management
- Optimization Modeling
Status: accepted
Back to the list of papers