Sparse Resource Allocation for Control of Spreading Processes via Convex Optimization

In this letter we propose a method for sparse allocation of resources to control spreading processes - such as epidemics and wildfires - using convex optimization, in particular exponential cone programming. Sparsity of allocation has advantages in situations where resources cannot easily be distributed over a large area. In addition, we introduce a model of risk to optimize the product of the likelihood and the future impact of an outbreak. We demonstrate with a simplified wildfire example that our method can provide more targeted resource allocation compared to previous approaches based on geometric programming.

Automated summary

This study presents a method for sparse allocation of resources to control spreading processes using convex optimization, particularly exponential cone programming. By introducing a risk model to optimize the product of the likelihood and future impact of an outbreak, the method can provide more targeted resource allocation. Experimental results with a simplified wildfire example show the effectiveness of this approach compared to previous geometric programming methods.