Counterexamples for BFGS-type methods under arbitrary strong Wolfe constants
Abstract: Whether the Broyden-Fletcher-Goldfarb-Shanno (BFGS) method and its variants can fail to converge on smooth nonconvex functions under realistic line-search parameters has remained a central open problem in quasi-Newton theory since the landmark counterexample of Dai (2002), which was confined to small Armijo parameters ( on Powell's geometry, or on his six-point cycle) and an objective function unbounded below. In this paper, we resolve the long-standing open question, posed by Dai (2002) following a discussion with J. C. Gilbert, of whether such counterexamples exist in theory for every Armijo parameter . Specifically, for every prescribed pair of line-search parameters $0 < c_1 < c_2 < 1$, we construct an objective function , bounded below and with Lipschitz continuous gradient, on which every method in a broad conjugacy class equipped with the first-local-minimizer line search generates an infinite sequence of iterates with for all . The class encompasses the classical full-memory BFGS method, limited-memory BFGS (L-BFGS) with arbitrary memory , the Broyden positive family, and the Hestenes-Stiefel conjugate gradient method. The steps are the standard first local minimizers along the search rays and simultaneously satisfy the strong Wolfe, weak Wolfe, Armijo, and Goldstein conditions with constants . The construction operates in the minimal possible dimension , exploiting a non-decaying conjugate descent orbit in the plane coupled with an explicit tubular interpolation whose two-bump axial curvature profile places the Armijo ratio anywhere in .
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