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分布魯棒二階隨機占優約束優化問題的穩定性

2023-04-08 16:15傅璐趙勇
關鍵詞:收斂性

傅璐 趙勇

摘要:

為規避真實分布的不確定性導致的風險,提出分布魯棒二階隨機占優約束優化問題,矩信息和Wasserstein球相結合構造分布集合,采用離散近似方法處理該問題,并在適當的假設條件下,討論近似問題可行集、最優值和最優解集的收斂性。

關鍵詞:二階隨機占優約束;分布魯棒優化;收斂性

中圖分類號:O224

文獻標志碼:A

二階隨機占優是決策論和經濟學中的基本概念,作為一種穩健的風險度量,理論上可以描述任何不確定的或隨機事件之間的優劣,做量化比較。在2003年,Dentcheva等[1]將二階隨機占優作為約束條件引入優化問題,研究了最優性條件和對偶理論。自此以后,許多學者對于二階隨機占優約束優化問題在最優性條件、靈敏度分析、算法等方面進行了大量研究[2-7]。但在很多實際問題中,決策者很難知道隨機變量真實分布的全部信息,因此,提出分布魯棒二階隨機占優約束優化問題,規避了真實分布的不確定性所帶來的風險[8-9]?,F有文獻多基于矩信息定義的分布集合或者基于以經驗分布為中心的Wasserstein球定義的分布集合,研究分布魯棒二階隨機占優約束優化問題的穩定性。由于分布集合的構造對研究分布魯棒優化問題非常重要,基于矩信息定義的分布集合不能刻畫分布集合的收斂性[10],基于以經驗分布為中心的Wasserstein球定義的分布集合克服了這個困難,卻又失去了滿足矩信息刻畫的分布[11]。在此基礎上,有研究改進了分布集合,提出將矩信息和Wasserstein球相結合構造分布集合,該集合不僅包含了更多的真實分布信息,又有效地排除病態分布[12]。目前,沒有文獻基于該分布集合研究分布魯棒二階隨機占優約束優化問題的穩定性。參考相關文獻[12],本文將基于矩信息和Wasserstein球相結合的分布集合,在適當的假設條件下,研究分布魯棒二階隨機占優約束優化問題的穩定性。

4 結論

本文基于矩信息和Wasserstein球相結合的分布集合,在適當的假設條件下,從定性、定量的角度討論了分布魯棒二階隨機占優約束優化問題可行集、最優值和最優解集的收斂性。后續將基于該分布集合,研究分布魯棒二階隨機占優約束優化問題的可處理形式,并將其應用到投資組合、供應鏈管理等實際問題。

參考文獻

[1]DENTCHEVA D, RUSZCZYN'SKI A. Optimization with stochastic dominance constraints[J]. SIAM Journal on Optimization, 2003, 14(2): 548-566.

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[5]張宏偉, 于海生, 龐麗萍, 等. 二階隨機占優約束優化問題的遺傳算法求解[J]. 大連理工大學學報, 2016, 56(3): 299-303.

[6]楊柳, 申飛飛. 考慮交易費用的二階隨機占優投資組合風險控制模型[J]. 應用概率統計, 2017, 33(2): 111-124.

[7]付永彬, 孫海琳. 二階隨機占優約束下考慮訂購能力的多產品報童問題[J]. 工程數學學報, 2020, 37(1): 1-15.

[8]GUO S Y, XU H F,ZHANG L W. Probability approximation schemes for stochastic programs with distributionally robust second-order dominance constraints[J]. Optimization Methods and Software, 2017, 32(4): 770-789.

[9]MEI Y, LIU J, CHEN Z P. Distributionally robust second-order stochastic dominance constrained optimization with Wasserstein ball[J]. SIAM Journal on Optimization, 2022, 32(2): 715-738.

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Stability of Distributionally Robust Second Order Stochastic Dominance Constrained Optimization Problem

FU Lu, ZHAO Yong

(College of Mathematics and Statistics, Chongqing Jiaotong University, Chongqing 400074, China)

Abstract:

In order to hedge the risks caused by the uncertainty of the true distribution, distributionally robust second order stochastic dominance constrained optimization problem was proposed, in which the ambiguity set was constructed based on the combination of moment information and Wasserstein ball. Then, the discrete approximation method was used to deal with the problem. Under appropriate assumptions, the convergence of the feasible set, the optimal value and the optimal solution set of the approximation problem was discussed.

Keywords:

second order stochastic dominance constrained; distributionally robust optimization; convergence

收稿日期:2023-06-27

基金項目:

重慶市自然科學基金面上項目(批準號:CSTB2022NSCQ-MSX1318)資助。

通信作者:

趙勇,男,博士,副教授,主要研究方向為隨機優化。E-mail: zhaoyongty@126.com

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