Inequality constrained stochastic nonlinear optimization via active-set sequential quadratic programming
We study nonlinear optimization problems with a stochastic objective and deterministic
equality and inequality constraints, which emerge in numerous applications including …
equality and inequality constraints, which emerge in numerous applications including …
A Sequential Quadratic Programming Method With High-Probability Complexity Bounds for Nonlinear Equality-Constrained Stochastic Optimization
A step-search sequential quadratic programming method is proposed for solving nonlinear
equality-constrained stochastic optimization problems. It is assumed that constraint function …
equality-constrained stochastic optimization problems. It is assumed that constraint function …
Sequential quadratic optimization for stochastic optimization with deterministic nonlinear inequality and equality constraints
A sequential quadratic optimization algorithm for minimizing an objective function defined by
an expectation subject to nonlinear inequality and equality constraints is proposed …
an expectation subject to nonlinear inequality and equality constraints is proposed …
Fully stochastic trust-region sequential quadratic programming for equality-constrained optimization problems
We propose a trust-region stochastic sequential quadratic programming algorithm (TR-
StoSQP) to solve nonlinear optimization problems with stochastic objectives and …
StoSQP) to solve nonlinear optimization problems with stochastic objectives and …
[HTML][HTML] Optimal control of thermoregulation in the human dermal regions investigated through the stochastic integrated techniques
In this research, stochastic computing techniques based on artificial neural networks are
applied to the proposed singular nonlinear differential equation to explain thermoregulation …
applied to the proposed singular nonlinear differential equation to explain thermoregulation …
[PDF][PDF] Asymptotic convergence rate and statistical inference for stochastic sequential quadratic programming
S Na, MW Mahoney - arXiv: 2205.13687 v1, 2022 - par.nsf.gov
We apply a stochastic sequential quadratic programming (StoSQP) algorithm to solve
constrained nonlinear optimization problems, where the objective is stochastic and the …
constrained nonlinear optimization problems, where the objective is stochastic and the …
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 …
Variance-reduced first-order methods for deterministically constrained stochastic nonconvex optimization with strong convergence guarantees
In this paper, we study a class of deterministically constrained stochastic optimization
problems. Existing methods typically aim to find an $\epsilon $-stochastic stationary point …
problems. Existing methods typically aim to find an $\epsilon $-stochastic stationary point …
Single-loop deterministic and stochastic interior-point algorithms for nonlinearly constrained optimization
An interior-point algorithm framework is proposed, analyzed, and tested for solving
nonlinearly constrained continuous optimization problems. The main setting of interest is …
nonlinearly constrained continuous optimization problems. The main setting of interest is …