A noise-tolerant SQP method with relaxations achieves global convergence and solution accuracy proportional to the noise level for inequality-constrained problems.
Design guidelines for noise-tolerant optimization with applications in robust design
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
math.OC 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
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.