We introduce Scylla, a primal heuristic for mixed-integer optimization problems. It exploits approximate solves of the Linear Programming relaxations through the matrix-free Primal-Dual Hybrid Gradient algorithm with specialized termination criteria, and derives integer-feasible solutions via fix-and-propagate procedures and feasibility-pump-like updates to the objective function. Computational experiments show that the method is particularly suited to instances with hard linear relaxations.

翻译：我们提出Scylla，一种用于混合整数优化问题的原始启发式算法。该方法利用无矩阵原始对偶混合梯度算法及其专门的终止准则，近似求解线性规划松弛问题，并通过固定传播过程以及对目标函数进行类可行性泵更新来获取整数可行解。计算实验表明，该方法特别适用于具有困难线性松弛的实例。