带条件风险价值的两阶段分布鲁棒优化模型的等价求解OA
A Solvable Model for Two-Stage Distributionally Robust Optimization with Conditional Value-at-Risk
在随机变量的分布信息不完全已知的情形下,利用随机变量的二阶矩信息来构造分布不确定集,进一步构建了一个带条件风险价值的两阶段分布鲁棒优化模型.在该模型的第二阶段问题目标函数的系数为随机变量时,借助锥对偶理论和极大极小原理将模型转化为可直接求解的半定规划问题.
This paper presents an equivalent solvable model for a two-stage distributionally robust optimi-zation(DRO)framework with Conditional Value-at-Risk(CVaR).Under the condition of incomplete in-formation regarding the distribution of random variables,an ambiguity set is constructed using the sec-ond-order moment information to establish the two-stage DRO-CVaR model.When the coefficients of the second-stage objective function are random variables,the model is transformed into a directly solvable semidefinite programming(SDP)problem by leveraging conic duality theory and the minimax principle.
刘英辉;韩有攀
西安工程大学理学院,陕西 西安 710600西安工程大学理学院,陕西 西安 710600
数理科学
条件风险价值分布鲁棒优化对偶理论半定规划
onditional value-at-riskdistributionally robust optimizationduality theorysemidefinite pro-gramming
《吉首大学学报（自然科学版）》 2026 (2)
18-23,6
陕西省自然科学基金资助项目(2025JC-YBM-099)
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