Code and Data Repository for Non-monotonicity of Branching Rules with Respect to Linear Relaxations
本软件通过随机生成的多维背包问题和MIPLIB 2017基准集上的切割实验，检验强分支规则在实际中非单调性的普遍性，发现切割闭合间隙较小时树规模变化难以预测且常增大，而闭合间隙足够大时树规模可能显著减小。
The goal of this software is to computationally ascertain how common it is for the strong branching rule to exhibit non-monotonicity in practice. We do so by applying cover cuts on randomly generated multi-dimensional knapsacks as well as by considering cuts applied by SCIP on MIPLIB 2017 benchmark set. Our main insight from these experiments is that if the gap closed by cuts is small, change in tree size is difficult to predict, and often increases, possibly due to inherent non-monotonicity. However, when a sufficiently large gap is closed, a significant decrease in tree size may be expected.