DISTRIBUTIONALLY ROBUST BILEVEL PROGRAMMING BASED ON WORST CONDITIONAL VALUE-AT-RISK

被引：0
|
作者：
Xu, Leiyan [1 ]
Shen, Rui [2 ]
Meng, Zhiqing [2 ]
机构：
[1] Nanjing Vocat Coll Informat Technol, Inst Digital Business, Nanjing 210023, Jiangsu, Peoples R China
[2] Zhejiang Univ Technol, Sch Econ, Hangzhou 310023, Zhejiang, Peoples R China
来源：
PACIFIC JOURNAL OF OPTIMIZATION | 2022年 / 18卷 / 04期
基金：
中国国家自然科学基金;
关键词：
distributionally robust bilevel programming; conditional value at risk; concave probability density distribution function cluster; PORTFOLIO SELECTION; OPTIMIZATION; UNCERTAINTY;
D O I：
暂无
中图分类号：
C93 [管理学]; O22 [运筹学];
学科分类号：
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要：
Distributionally robust bilevel programming based on worst conditional value at risk(WCVaR) is a decision model composed of upper and lower objective functions under WCVaR. First, a concave probability density distribution cluster describing random fluctuation is defined. Then the structure of distributionally robust bilevel programming based on WCVaR with the concave probability density distribution cluster is defined, where both the upper and the lower objective function of the model include WCVaR measures. It is proved that this distributionally robust bilevel programming can be approximately equivalently expressed as robust bilevel programming with parameters, which provides us with an approximate method to solve distributionally robust optimization based on WCVaR with the concave probability density distribution cluster.
引用
收藏
页码：825 / 839
页数：15
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