论文标题
具有新的二次决策规则的两阶段可调节鲁棒线性程序的确切圆锥编程重新进行
Exact Conic Programming Reformulations of Two-Stage Adjustable Robust Linear Programs with New Quadratic Decision Rules
论文作者
论文摘要
在本文中，我们介绍了一项新的参数化二次决策规则（QDR），即对两阶段的可调可调的可调式可调优化问题的常用仿射决策规则（ADR）的概括（ADR），并表明（亲密参数化的）可调节的可调式可调性优化问题（QDR）是数值的QDR，QDR是数值的connitient and QDR，SDER conne conne and Programe（SDEF）con（SDEF）（SD）（SDEF）（SDEF）（SD）（SDEF）（SD）（SDEFINE）（SDEFINE）（SDEF）（SDEF）。 （SOCP）重新制定。在这些QDR下，我们还确定了确切的圆锥程序重新纠正也适用于两阶段的线性ARO问题，其中还包含其目标功能中的可调节变量。然后，我们通过数值实验显示了不确定需求的批量大小问题，即在最坏的意义和模拟实现不确定需求相对于真实解决方案的不确定需求之后，QDR的可调稳健线性优化问题都可以改善其性能的ADR。
In this paper we introduce a new parameterized Quadratic Decision Rule (QDR), a generalisation of the commonly employed Affine Decision Rule (ADR), for two-stage linear adjustable robust optimization problems with ellipsoidal uncertainty and show that (affinely parameterized) linear adjustable robust optimization problems with QDRs are numerically tractable by presenting exact semi-definite program (SDP) and second order cone program (SOCP) reformulations. Under these QDRs, we also establish that exact conic program reformulations also hold for two-stage linear ARO problems, containing also adjustable variables in their objective functions. We then show via numerical experiments on lot-sizing problems with uncertain demand that adjustable robust linear optimization problems with QDRs improve upon the ADRs in their performance both in the worst-case sense and after simulated realization of the uncertain demand relative to the true solution.
