Spanning and splitting: Integer semidefinite programming for the quadratic minimum spanning tree problem
针对二次最小生成树问题，提出一种混合整数半定规划模型，利用代数连通性推导出双重非负松弛，并开发Peaceman-Rachford分裂方法求解，显著提升了大规模图（超过30个顶点）的界值质量和计算时间。
In the quadratic minimum spanning tree problem (QMSTP) one wants to find the minimizer of a quadratic function over all possible spanning trees of a graph. We present a formulation of the QMSTP as a mixed-integer semidefinite program exploiting the algebraic connectivity of a graph. Based on this formulation, we derive a doubly nonnegative relaxation for the QMSTP and investigate classes of valid inequalities to strengthen the relaxation using the Chvátal-Gomory procedure for mixed-integer conic programming.<br/>Solving the resulting relaxations is out of reach for off-the-shelf software. We therefore develop and implement a version of the Peaceman-Rachford splitting method that allows to compute the new bounds for graphs from the literature. The computational results demonstrate that our bounds significantly improve over existing bounds from the literature in both quality and computation time, in particular for graphs with more than 30 vertices.<br/>This work is further evidence that semidefinite programming is a valuable tool to obtain high-quality bounds for problems in combinatorial optimization, in particular for those that can be modelled as a quadratic problem.