Stochastic optimization of regenerative systems using infinitesimalperturbation analysis

We consider the problem of optimizing the steady-state mean of a controlled regenerative process using a stochastic optimization algorithm driven by infinitesimal perturbation analysis (IPA) derivative estimates. We derive IPA derivative estimates for our problem and prove almost sure convergence of the algorithm. The generality of our formulation should encompass a wide variety of practical systems. We illustrate our framework and results via several examples