A stochastic sequential quadratic optimization algorithm for nonlinear-equality-constrained optimization with rank-deficient Jacobians
A sequential quadratic optimization algorithm is proposed for solving smooth nonlinear-
equality-constrained optimization problems in which the objective function is defined by an …
equality-constrained optimization problems in which the objective function is defined by an …
Inexact sequential quadratic optimization for minimizing a stochastic objective function subject to deterministic nonlinear equality constraints
An algorithm is proposed, analyzed, and tested experimentally for solving stochastic
optimization problems in which the decision variables are constrained to satisfy equations …
optimization problems in which the decision variables are constrained to satisfy equations …
Matrix-free interior point method
J Gondzio - Computational Optimization and Applications, 2012 - Springer
In this paper we present a redesign of a linear algebra kernel of an interior point method to
avoid the explicit use of problem matrices. The only access to the original problem data …
avoid the explicit use of problem matrices. The only access to the original problem data …
[PDF][PDF] Numerical simulation methods for embedded optimization
R Quirynen - 2017 - researchgate.net
Our quality of life, the world's productivity and its sustainability become more and more
determined by the outcome and benefits of process automation. In this domain of automatic …
determined by the outcome and benefits of process automation. In this domain of automatic …
An interior-point algorithm for large-scale nonlinear optimization with inexact step computations
We present a line-search algorithm for large-scale continuous optimization. The algorithm is
matrix-free in that it does not require the factorization of derivative matrices. Instead, it uses …
matrix-free in that it does not require the factorization of derivative matrices. Instead, it uses …
An adaptive sampling sequential quadratic programming method for equality constrained stochastic optimization
This paper presents a methodology for using varying sample sizes in sequential quadratic
programming (SQP) methods for solving equality constrained stochastic optimization …
programming (SQP) methods for solving equality constrained stochastic optimization …
A sequential quadratic programming method for optimization with stochastic objective functions, deterministic inequality constraints and robust subproblems
S Qiu, V Kungurtsev - arXiv preprint arXiv:2302.07947, 2023 - arxiv.org
In this paper, a robust sequential quadratic programming method of [1] for constrained
optimization is generalized to problem with stochastic objective function, deterministic …
optimization is generalized to problem with stochastic objective function, deterministic …
A first-order numerical algorithm without matrix operations
This paper offers a matrix-free first-order numerical method to solve large-scale conic
optimization problems. Solving systems of linear equations pose the most computationally …
optimization problems. Solving systems of linear equations pose the most computationally …
A note on the implementation of an interior-point algorithm for nonlinear optimization with inexact step computations
This paper describes an implementation of an interior-point algorithm for large-scale
nonlinear optimization. It is based on the algorithm proposed by Curtis et al.(SIAM J Sci …
nonlinear optimization. It is based on the algorithm proposed by Curtis et al.(SIAM J Sci …
An inertia-free filter line-search algorithm for large-scale nonlinear programming
We present a filter line-search algorithm that does not require inertia information of the linear
system. This feature enables the use of a wide range of linear algebra strategies and …
system. This feature enables the use of a wide range of linear algebra strategies and …