论文标题
通过灵敏度分析，概率保证情景方法的客观价值
Probabilistic guarantees on the objective value for the scenario approach via sensitivity analysis
论文作者
论文摘要
本文涉及场景方法的客观价值性能，以进行稳健的凸优化。提出了一种新的方法，以从具有有限数量的样本的场景程序中得出客观值的概率界限。这种方法依赖于最大的重新印象和强大优化问题的复杂性的概念。通过额外的连续性和规律性条件，通过灵敏度分析，我们还提供明确的界限，从而超过了文献中现有的结果。为了说明结果的改进，我们还提供了一个数值示例。
This paper is concerned with objective value performance of the scenario approach for robust convex optimization. A novel method is proposed to derive probabilistic bounds for the objective value from scenario programs with a finite number of samples. This method relies on a max-min reformulation and the concept of complexity of robust optimization problems. With additional continuity and regularity conditions, via sensitivity analysis, we also provide explicit bounds which outperform an existing result in the literature. To illustrate the improvements of our results, we also provide a numerical example.
