Distributionally robust optimization with matrix moment constraints: Lagrange duality and cutting plane methods

Distributionally robust optimization with matrix moment constraints: Lagrange duality and cutting plane methods
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具有矩阵矩约束的分布鲁棒优化:拉格朗日对偶性和割平面方法

DOI:
10.1007/s10107-017-1143-6
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发表时间:
2017-04
期刊:
Math. Program.
影响因子:
--
通讯作者:
Hailin Sun
Hailin Sun
中科院分区:
其他
文献类型:
--
作者:
Huifu Xu;Yongchao Liu;Hailin Sun

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求解极小极大分布鲁棒优化问题的一个关键步骤是将内部极大值w.r.t.通过拉格朗日对偶将概率测度转化为半无限规划问题。斯莱特型条件已被广泛用于强对偶(零对偶间隙)时的模糊度集定义通过时刻。本文研究了证明斯莱特型条件的有效方法,并引入了基于内极大化问题最优值函数的下连续性的其它条件。此外,我们提出了两个离散化方案,解决DRO与一个对偶DRO和其他直接通过DRO的模糊集。在没有强对偶的情况下,通过拉格朗日对偶的离散化方案可以提供DRO的最优值的上限,而直接离散化方法提供下限。因此,提出了两个切割平面方案:一个离散化的对偶DRO和其他的离散模糊度集的极大极小DRO。从最优值、最优解和不动点三个方面对逼近格式进行了收敛性分析。比较的数值结果报告所产生的算法。
A key step in solving minimax distributionally robust optimization (DRO) problems is to reformulate the inner maximization w.r.t. probability measure as a semiinfinite programming problem through Lagrange dual. Slater type conditions have been widely used for strong duality (zero dual gap) when the ambiguity set is defined through moments. In this paper, we investigate effective ways for verifying the Slater type conditions and introduce other conditions which are based on lower semicontinuity of the optimal value function of the inner maximization problem. Moreover, we propose two discretization schemes for solving the DRO with one for the dualized DRO and the other directly through the ambiguity set of the DRO. In the absence of strong duality, the discretization scheme via Lagrange duality may provide an upper bound for the optimal value of the DRO whereas the direct discretization approach provides a lower bound. Two cutting plane schemes are consequently proposed: one for the discretized dualized DRO and the other for the minimax DRO with discretized ambiguity set. Convergence analysis is presented for the approximation schemes in terms of the optimal value, optimal solutions and stationary points. Comparative numerical results are reported for the resulting algorithms.
DOI: 10.1137/s0040585x97986850
发表时间: 2012-06
期刊: arXiv: Probability
影响因子: --
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DOI: 10.1287/opre.2014.1314
发表时间: 2014-12
期刊: Oper. Res.
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