Troltzsch: Analysis of the Lagrange-SQP-Newton method for the control of a Phase field equation
, 1999 This paper investigates the local convergence of the Lagrange–SQP–Newton method applied to an optimal control problem governed by a phase field equation with distributed control.
Matthias Heinkenschloss +1 more
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Tensor methods for finding approximate stationary points of convex functions. [PDF]
Optim Methods Softw, 2022 Grapiglia GN, Nesterov Y.
europepmc +1 more source
Trust Region Affine Scaling Algorithms for Linearly Constrained Convex and Concave Programs
, 1996 We study a trust region affine scaling algorithm for solving the linearly constrained convex or concave programming problem. Under primal nondegeneracy assumption, we prove that every accumulation point of the sequence generated by the algorithm ...
Yanhui Wang, Renato D.C. Monteiro
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Minimizing Uniformly Convex Functions by Cubic Regularization of Newton Method. [PDF]
J Optim Theory Appl, 2021 Doikov N, Nesterov Y.
europepmc +1 more source
Isotropic Effective Energy Simulated Annealing Searches for Low Energy Molecular Cluster States
, 1992 . The search for low energy states of molecular clusters is associated with the study of molecular conformation and especially protein folding. This paper describes a new global minimization algorithm which is effective and efficient for finding low ...
Thomas Coleman +5 more
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Forecasting the action of CAR-T cells against SARS-corona virus-II infection with branching process. [PDF]
Model Earth Syst Environ, 2022 Al-Utaibi KA +5 more
europepmc +1 more source
A cyclic iterative method for solving multiple sets split feasibility problems in Banach spaces
, 2016 In this paper, we construct an iterative scheme and prove strong convergence theorem of the sequence generated to an approximate solution to a multiple sets split feasibility problem in a p-uniformly convex and uniformly smooth real Banach space.
Shehu, Y, Iyiola, O.S.
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A globally convergent linearly constrained Lagrangian method for nonlineary constrained optimization
, 2002 . For optimization problems with nonlinear constraints, linearly constrained Lagran-gian (LCL) methods solve a sequence of subproblems of the form \minimize an augmented Lagrangian function subject to linearized constraints".
Michael P. Friedlander +2 more
core
Gradient Methods on Strongly Convex Feasible Sets and Optimal Control of Affine Systems. [PDF]
Appl Math Optim, 2020 Veliov VM, Vuong PT.
europepmc +1 more source
Hybrid proximal linearized algorithm for the split DC program in infinite-dimensional real Hilbert spaces. [PDF]
J Inequal Appl, 2018 Chuang CS, Yang PJ.
europepmc +1 more source