A nonsmooth nonconvex descent algorithm
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The paper presents a new descent algorithm for locally Lipschitz continuous functions f:X→R. The selection of a descent direction at some iteration point x combines an approximation of the set-valued gradient of f on a suitable neighborhood of x (recently introduced by Mankau Schuricht) with an Armijo type step control. The algorithm is analytically justified and it is shown that accumulation points of iteration points are critical points of f. Finally the algorithm is tested for numerous benchmark problems and the results are compared with simulations found in the literature.
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