Convergence of adaptive minimization algorithms for objective function minimum drift

We develop algorithms for the search and tracking of the drift minimum of an objective function with linear stationary drift. We give an analytic estimate for the properties of the methods, obtain conditions for the approximation of a simplex to a drift minimum as well as relations for the design of algorithms with the desired properties, and prove a theorem on the convergence of the algorithms. We give the results of a numerical experiment.