Robust optimal control of deterministic information epidemics with noisy transition rates

In this paper the robust optimal control of deterministic information epidemics is inspected taking into consideration the noisy transition rates. Distinct from conventional works, the heterogeneous susceptible–infected–susceptible (SIS) model is adopted where both the heterogeneities in the network topology and the individual diversity are considered. In light of the commonly existing noise in the transition processes, we address the robust optimal control problem aiming at maximizing the spreading performance at the finite time instant given a fixed budget. By using the distribution analysis techniques, the inspected problem is transformed to a constrained optimal control problem and solved by the Pontryagin Maximum Principle (PMP). A novel approach combining the forward–backward sweep method and the secant method is proposed to efficiently reduce the computation burden. The performance of the robust optimal control as well as the influence of the parameters is examined by numerical experiments in real social networks.