基于流的方法用于消失约束问题
A Flow-based Method for Problems with Vanishing Constraints
AI总结：
本文提出了一种基于分段梯度流的方法，用于解决具有消失约束的数学规划问题，通过达到一阶 stationary 点来提高求解效率，并在实际案例中验证了其有效性。
摘要：
数学规划中的消失约束问题（MPVCs）是一类极具挑战性的问题，因其缺乏约束资格条件。因此，为解决这些问题，通常采用松弛方法。虽然通常能取得满意的结果，但它们通常需要大量的手动调整和松弛参数的调整。为克服这些问题，我们介绍了一种基于分段梯度流的新方法，以达到一阶 stationary 点。我们在几个现实世界中的 MPVC 实例上展示了我们方法的有效性，并将其与一种常见的松弛方法进行了比较。
英文摘要：
Mathematical Programs with Vanishing Constraints (MPVCs) are a notoriously challenging class of problems owing to their lack of constraint qualification. Therefore, to tackle these problems, relaxation-based approaches are typically used. While often yielding satisfactory results, they generally require significant manual tuning and adjustment of the relaxation parameter. To circumvent these problems, we introduce a novel approach based on piecewise gradient flows leading to first-order stationary points. We demonstrate the effectiveness of our method on several real-world MPVC instances and compare it to a common relaxation approach.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
