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
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Gradient Methods on Strongly Convex Feasible Sets and Optimal Control of Affine Systems. [PDF]
Appl Math Optim, 2020 Veliov VM, Vuong PT.
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Hybrid proximal linearized algorithm for the split DC program in infinite-dimensional real Hilbert spaces. [PDF]
J Inequal Appl, 2018 Chuang CS, Yang PJ.
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Estimation and optimal control of the multi-scale dynamics of the Covid-19
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An algorithm for the split-feasibility problems with application to the split-equality problem. [PDF]
J Inequal Appl, 2017 Chuang CS, Chen CM.
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A class of derivative-free trust-region methods with interior backtracking technique for nonlinear optimization problems subject to linear inequality constraints. [PDF]
J Inequal Appl, 2018 Gao J, Cao J.
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Primal-dual interior point QP-free algorithm for nonlinear constrained optimization. [PDF]
J Inequal Appl, 2017 Jian J, Zeng H, Ma G, Zhu Z.
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An SQP method for mathematical programs with vanishing constraints with strong convergence properties. [PDF]
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Gradient regularization of Newton method with Bregman distances. [PDF]
Math ProgramDoikov N, Nesterov Y.
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