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A Lagrangian Dual Method with Self-Concordant Barriers for Multi-Stage Stochastic Convex Programming

机译:多阶段随机凸规划的带有自协调障碍的拉格朗日对偶方法

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摘要

This paper presents an algorithm for solving multi-stage stochastic convex nonlinear programs. The algorithm is based on the Lagrangian dual method which relaxes the nonanticipativity constraints, and the barrier function method which enhances the smoothness of the dual objective function so that the Newton search directions can be used. The algorithm is shown to be of global convergence and of polynomial-time complexity.
机译:本文提出了一种求解多阶段随机凸非线性程序的算法。该算法基于放宽非预期约束的拉格朗日对偶方法和屏障函数方法,该方法提高了对偶目标函数的平滑度,从而可以使用牛顿搜索方向。该算法被证明具有全局收敛性和多项式时间复杂度。

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