Asymptotic Analysis for a Stochastic Second-Order Cone Programming and Applications

Author:

Zhang Jie1,Shi Yue1,Tong Mengmeng2,Li Siying1

Affiliation:

1. School of Mathematics, Liaoning Normal, University, Dalian 116029, P. R. China

2. School of Management Science and Engineering, Dongbei University of Finance and Economics, Dalian 116025, P. R. China

Abstract

Stochastic second-order cone programming (SSOCP) is an extension of deterministic second-order cone programming, which demonstrates underlying uncertainties in practical problems arising in economics engineering and operations management. In this paper, asymptotic analysis of sample average approximation estimator for SSOCP is established. Conditions ensuring the asymptotic normality of sample average approximation estimators for SSOCP are obtained and the corresponding covariance matrix is described in a closed form. Based on the analysis, the method to estimate the confidence region of a stationary point of SSOCP is provided and three examples are illustrated to show the applications of the method.

Funder

National Natural Science Foundation of China

Liaoning Revitalization Talents Program

Scientific Research Fund of Liaoning Provincial Education Department

Natural Science Foundation of Liaoning Province

Publisher

World Scientific Pub Co Pte Ltd

Subject

Management Science and Operations Research,Management Science and Operations Research

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