Since 1980, the yearly number of natural disasters has more than doubled. Oftentimes, these disasters leave many people homeless and without resources, so it’s important that relief organizations maximize their efforts when responding to such events. This is especially true recently, with Hurricane Harvey wrecking Texas, Hurricane Irma pummeling the Caribbean, and an 8.2 magnitude earthquake rattling Mexico just this month.
A recent paper published through Elsevier (link above) examines the efficiency of relief organizations at face value and attempts to develop what they believe to be the first Generalized Nash Equilibrium model for post-disaster humanitarian relief. The paper points out that little research has gone into improving the efforts of non-governmental relief organizations (NGOs) previously, and that many have worried that these organizations are ineffective due to lack of coordination. The paper tackles these issues by analyzing the network below:
This model represents the allocation of a certain relief item to n demand points from m NGOs that receive donations from D. The paper creates a utility function for NGOs dependent on the amount of relief item going to each location, the cost it will take to provide the items at each location. Since this is a Generalized Nash Equilibrium, the strategies of the NGOs depend on each other, ensuring that NGOs don’t undersupply or oversupply any of the demand points. Ultimately, the paper determines through a few examples and a case study of Hurricane Katrina that the use of the Generalized Nash Equilibrium is superior to that of a Nash Equilibrium, because it accounts for the amount of relief supplied by any given organization to each location. This implies that cooperation is essential to improve efficiency of relief organizations.
It’s clear from reading the article that the Game Theory used by the author is much more complicated than the topics we’ve covered in class, but there are still comparisons to be made. The paper creates a network for the organizations, and then essentially finds a Nash equilibrium for that network to determine the amount of a relief item to be sent to each location from each organization. The only difference is that the strategies now depend on each other’s strategies, so the assumption that the players can’t communicate is essentially made void.