A Nonmonotone Trust Region Method for Unconstrained Optimization Problems on Riemannian Manifolds

Xiaobo Li (), Xianfu Wang () and Manish Krishan Lal ()
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Xiaobo Li: Southwest Petroleum University
Xianfu Wang: University of British Columbia Okanagan
Manish Krishan Lal: University of British Columbia Okanagan

Journal of Optimization Theory and Applications, 2021, vol. 188, issue 2, No 12, 547-570

Abstract: Abstract We propose a nonmonotone trust region method for unconstrained optimization problems on Riemannian manifolds. Global convergence to the first-order stationary points is proved under some reasonable conditions. We also establish local R-linear, super-linear and quadratic convergence rates. Preliminary experiments show that the algorithm is efficient.

Keywords: Unconstrained optimization; Nonmonotone technique; Trust region method; Convergence rate; Riemannian manifolds; 65K05; 65K10; 90C48; 49J40 (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s10957-020-01796-6

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