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ROBIST: Robust optimization by iterative scenario sampling and statistical testing
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DOI：10.1016/j.cor.2025.107260.png)
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Abstract
En 中文
• Simple and effective data-driven algorithm for optimization under uncertainty. • Applicable to wide variety of stochastic optimization problems. • Numerical experiments demonstrate superior performance in comparison to alternative methods. • Python package publicly available, see https://github.com/JustinStarreveld/ROBIST .
Keywords:
90C15
90C17
Optimization
Uncertainty
Stochastic
Robust
Data-driven
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