Designing Sensor Networks by a Generalized Highly Optimized Tolerance Model

Abstract

A variant of the highly optimized tolerance model is applied to a toy problem of bioterrorism to determine the optimal arrangement of hypothetical bio-sensors to avert epidemic outbreak. Nonlinear loss function is utilized in searching the optimal structure of the sensor network. The proposed method successfully averts disastrously large events, which can not be achieved by the original highly optimized tolerance model.