The paper proposes a novel class of quadratically constrained convex reformulations (QCCR) for semi-continuous quadratic programming. We first propose the class of QCCR for the studied problem. Next, we discuss how to polynomially find the best reformulation corresponding with the tightest continuous bound within this class. The properties of the proposed QCCR are then studied. Finally, preliminary computational experiments are conducted to illustrate the effectiveness of the proposed approach.

中文翻译：

---

用于半连续二次规划的更严格二次约束凸重构

该论文提出了一种用于半连续二次规划的新型二次约束凸重构 (QCCR)。我们首先为所研究的问题提出 QCCR 类。接下来，我们讨论如何以多项式的方式找到与此类中最紧密的连续边界相对应的最佳重构。然后研究了所提出的 QCCR 的特性。最后，进行了初步的计算实验来说明所提出方法的有效性。