A trust-region strategy for minimization on arbitrary domains

The authors present a trust-region method for minimizing a general differentiable function restricted to an arbitrary closed set. They prove a global convergence theorem. The trust-region method defines difficult subproblems that are solvable in some particular cases. The authors analyze in detail the case where the domain is a Euclidean ball. For this case they present numerical experiments where the authors consider different Hessian approximations.