Synthetic QCQP Data

该数据集是为了演示所提出的一种针对稳健凸二次约束二次规划（QCQP）算法而生成的合成数据。它包含了问题系数和不确定性集合。此外，数据集不仅包含一个无上下文实例，还包含了一个具有不同不确定性集合的上下文优化问题。数据集按规模分为五种问题大小，每种大小包含五个约束，并随机生成系数。该任务旨在研究在上下文设置中使用决策聚焦学习的稳健优化方法。

This synthetic dataset is generated to demonstrate the proposed algorithm for robust convex quadratically constrained quadratic programming (QCQP). It includes problem coefficients and uncertainty sets. Furthermore, the dataset contains not only a context-free instance but also a contextual optimization problem with different uncertainty sets. The dataset is categorized into five problem sizes, each of which contains five constraints with randomly generated coefficients. This task aims to investigate robust optimization methods that employ decision-focused learning in contextual settings.