The Polyhedral Active Set Algorithm (PASA) is designed to optimize a general nonlinear function over a polyhedron. Phase one of the algorithm is a nonmonotone gradient projection algorithm, while phase two is an active set algorithm that explores faces of the constraint polyhedron. A gradient-based implementation is presented, where a projected version of the conjugate gradient algorithm is employed in phase two. Asymptotically, only phase two is performed. Comparisons are given with IPOPT using polyhedral-constrained problems from CUTEst and the Maros/Meszaros quadratic programming test set.

中文翻译：

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算法 1035：多面体活动集算法的基于梯度的实现

多面体活动集算法 (PASA) 旨在优化多面体上的一般非线性函数。该算法的第一阶段是非单调梯度投影算法，而第二阶段是探索约束多面体的面的活动集算法。提出了基于梯度的实现，其中在第二阶段采用共轭梯度算法的投影版本。渐进地，仅执行第二阶段。使用 CUTEst 和 Maros/Meszaros 二次规划测试集的多面体约束问题与 IPOPT 进行比较。