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Operations Research Transactions >

2022 , Vol. 26 >Issue 2: 31 - 44

DOI: https://doi.org/10.15960/j.cnki.issn.1007-6093.2022.02.003

An SAA approach for a class of second-order cone stochastic inverse quadratic programming problem

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  • 1. Key Laboratory of Operations Research and Control of Universities in Fujian, School of Mathematics and Statistics, Fuzhou University, Fuzhou 350116, Fujian, China
    2. College of Computer Science and Mathematics, Fujian University of Technology, Fuzhou 350118, Fujian, China
    3. School of Mathematical Sciences, Dalian University of Technology, Dalian 116024, Liaoning, China

Received date: 2020-06-23

  Online published: 2022-05-27

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Abstract

In this paper, we consider a class of stochastic inverse quadratic second-order cone programming problem. This stochastic model contains complementarity constraints, and is more proper to model some class of real world problems. By employing the techniques of stochastic sampling and smoothing, we construct auxiliary approximate sub-problems to solve the original model. In addition, we proved that if the solutions of the approximate sub-problems converge, then with probability one the limit is the C-stationary point of the original problem. If strict complementarity condition and the second order necessary condition hold, then with probability one the limit is an M-stationary point. A simple numerical test verified the applicability of our approach.

Key words： stochastic sampling; complementarity constraint; second-order cone programming

Cite this article

Bo WANG, Li CHU, Liwei ZHANG, Hongwei ZHANG . An SAA approach for a class of second-order cone stochastic inverse quadratic programming problem[J]. Operations Research Transactions, 2022 , 26(2) : 31 -44 . DOI: 10.15960/j.cnki.issn.1007-6093.2022.02.003

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