Iteration-complexity and asymptotic analysis of steepest descent method for multiobjective optimization on Riemannian manifolds
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Publication:2302754
DOI10.1007/s10957-019-01615-7zbMath1432.90137arXiv1906.05975OpenAlexW2992083372WikidataQ115382545 ScholiaQ115382545MaRDI QIDQ2302754
Maurício Silva Louzeiro, L. F. Prudente, Orizon P. Ferreira
Publication date: 26 February 2020
Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1906.05975
Riemannian manifoldsteepest descent methodmultiobjective optimization problemiteration-complexity boundlower bounded curvature
Numerical mathematical programming methods (65K05) Multi-objective and goal programming (90C29) Complementarity and equilibrium problems and variational inequalities (finite dimensions) (aspects of mathematical programming) (90C33)
Related Items (8)
On \(q\)-steepest descent method for unconstrained multiobjective optimization problems ⋮ Riemannian Conjugate Gradient Methods: General Framework and Specific Algorithms with Convergence Analyses ⋮ A trust region method for solving multicriteria optimization problems on Riemannian manifolds ⋮ Complexity bound of trust-region methods for convex smooth unconstrained multiobjective optimization ⋮ Convergence of inexact steepest descent algorithm for multiobjective optimizations on Riemannian manifolds without curvature constraints ⋮ Inexact proximal point algorithm for quasiconvex optimization problems on Hadamard manifolds ⋮ Multiobjective BFGS method for optimization on Riemannian manifolds ⋮ A generalized geometric spectral conjugate gradient algorithm for finding zero of a monotone tangent vector field on a constant curvature Hadamard manifold
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