We describe an extension of the classical cutting plane algorithm to tackle the unconstrained minimization of a nonconvex, not necessarily differentiable function of several variables. The method is based on the construction of both a lower and an upper polyhedral approximation to the objective function and it is related to the use of the concept of proximal trajectory. Convergence to a stationary point is proved for locally Lipschitz functions.
Citation
SIAM Journal on Optimization, 14(3), 743-756, 2004.