A Subgrudient Method for Unconstrained Nonconvex Nonsmooth Optimization

Morteza Maleknia

Abstract


We propose an iterative method that solves an unconstrained nonconvex nonsmooth optimization problem. The proposed method is a descent method that uses subgradients at each iteration and contains a very simple procedures for finding descent directions and for solving line search subproblems. The convergence of the algorithms will be studied.

Keywords


Nonsmooth Optimization, Subgradient Method

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