A noise-tolerant SQP method with relaxations achieves global convergence and solution accuracy proportional to the noise level for inequality-constrained problems.
An interior-point algorithm for large-scale nonlinear optimization with inexact step computations.SIAM Journal on Scientific Computing, 32(6):3447–3475
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A Noise Tolerant SQP Algorithm for Inequality Constrained Optimization
A noise-tolerant SQP method with relaxations achieves global convergence and solution accuracy proportional to the noise level for inequality-constrained problems.