Regularized linearization method with errors in the initial data (Q1085071)

To solve the minimization problem with inequality-type constraints, the authors propose a regularized linearization method under conditions such that the function to be minimized and the functional specifying the set, and their gradients, are known with errors. For convex problems, it is shown that the method converges to the solution with minimum norm.