研究人员开发了GraphBU，一种用于创建混合整数线性规划（MILP）实例的新型图原生生成器。该方法利用具有接口的局部子问题作为基本单元，促进节点与主约束或边界变量的耦合。GraphBU旨在保留MILP实例的结构属性，这对于求解器开发和训练学习策略至关重要。该生成器在保持与源系列相似的图统计数据、在数据集中保留可行性以及改进下游的预测与搜索训练方面已取得成功。 AI
影响 改进了用于优化中机器学习模型训练的结构化数据的生成。
排序理由 该集群包含一篇详细介绍生成MILP实例新方法的论文。
AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →
arXiv:2607.06532v1 Announce Type: new Abstract: Mixed-integer linear programming (MILP) instances used for solver development are hard to obtain when models come from private or application-specific pipelines. A generator must keep the structure that solvers and learned policies …
Mixed-integer linear programming (MILP) instances used for solver development are hard to obtain when models come from private or application-specific pipelines. A generator must keep the structure that solvers and learned policies rely on. Existing general generators usually cho…