Generating proactive humanitarian aid networks with guided topology and small-world effect

Abstract

Humanitarian aid works are highly required for rescue, damage control, early recovery and integrated rehabilitation after disasters occur. There are various entities and actors of various mandates, sizes, capacities and expertise in post-disaster aid environment. Humanitarian aid work consists of multi-actors' activities and the actors communicate as well as share information among themselves. Hence, a network of aid actors is formed in post-disaster environment. The inter-organizational relationships among heterogeneous actors in post-disaster intervention are complex in terms of coordination and communication. Optimization and controlling the topology of these aid actors' networks can help to ensure the proper coordination, timely information flow and feasible aid flow in post-disaster scenarios. In this study, we propose an algorithm to proactively generate a network of the humanitarian aid actors in post-disaster settings which is a complex network with power law degree distribution, desired small world effects and high clustering coefficient. Our experiments show that networks generated by our algorithm are random failure-tolerant and scale-free and the dynamism of the network is easily predictable as well as controllable via the high degree hub nodes.