Mathematical models for decision-making support in humanitarian logistics and aid operations

Abstract

Natural disasters constitute a constant threat to human populations, and their impact can generate a deterioration in the short, medium, and long term in the affected population’s wellbeing and life quality. In particular, landslides and floods are disasters with an incidence among Colombian populations that are located near bodies of water or mountain ranges, annually impacting thousands of inhabitants who are forced to either abandon their places of residence or experience shortages of products such as food and medicines. Within the aid efforts, several activities are carried out as part of the disaster mitigation plans, such as transportation operations, and inventory management that are framed into the humanitarian response. This research addresses three main challenges within humanitarian operations related to storage and goods delivery and proposes a wide and robust framework to support the decision-making process during humanitarian operations. Two simulation models based on system dynamics are proposed to deal with the evaluation of the interactions between actors in the humanitarian supply chain as well as evaluate the consequences on the road network caused by food delivery tasks to the affected populations. The proposed models were validated using the available recorded information of two major landslide disasters that occurred in Colombia in 2017 in the Mocoa and Rosas municipalities, respectively.