An exact primal–dual penalty method approach to warmstarting interior-point methods for linear programming
An exact primal–dual penalty method approach to warmstarting interior-point methods for linear programming
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DOI：
10.1007/s10589-007-9048-6
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发表时间：
2007-12
影响因子：
2.2
通讯作者：
Hande Y. Benson;D. Shanno
中科院分区：
文献类型：
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作者：
Hande Y. Benson;D. Shanno
与活动集方法相比，邻近点方法的一个明显缺陷是它们不能通过在热启动后解决密切相关的问题来有效地重新优化。在本文中，我们研究了使用原始-对偶惩罚方法来克服这个问题。我们证明了精确性和收敛性，并在一组线性和混合整数规划问题上显示出令人鼓舞的数值结果。
One perceived deficiency of interior-point methods in comparison to active set methods is their inability to efficiently re-optimize by solving closely related problems after a warmstart. In this paper, we investigate the use of a primal–dual penalty approach to overcome this problem. We prove exactness and convergence and show encouraging numerical results on a set of linear and mixed integer programming problems.