A proximal limited-memory quasi-Newton scheme is developed for nonsmooth nonconvex optimization, with global convergence proven under mild assumptions and rates under the Kurdyka-Lojasiewicz property.
Byrd, Jorge Nocedal, and Robert B
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A Riemannian L-BFGS method with adapted Cauchy-point bound handling outperforms classical interior-point and L-BFGS-B solvers on mixed manifold-plus-bounds problems by orders of magnitude.
Analytical gradients and Hessian for low-thrust rendezvous Δv enable efficient nonlinear programming of multi-asteroid trajectories.
citing papers explorer
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Proximal Limited-Memory Quasi-Newton Methods for Nonsmooth Nonconvex Optimization
A proximal limited-memory quasi-Newton scheme is developed for nonsmooth nonconvex optimization, with global convergence proven under mild assumptions and rates under the Kurdyka-Lojasiewicz property.
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A Riemannian quasi-Newton algorithm for optimization with Euclidean bounds
A Riemannian L-BFGS method with adapted Cauchy-point bound handling outperforms classical interior-point and L-BFGS-B solvers on mixed manifold-plus-bounds problems by orders of magnitude.
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Nonlinear Programming of Low-Thrust Multi-Rendezvous Trajectories Using Analytical Hessian
Analytical gradients and Hessian for low-thrust rendezvous Δv enable efficient nonlinear programming of multi-asteroid trajectories.