Stochastic second-order-cone complementarity problems: expected residual minimization formulation and its applications

Gui Hua Lin*, Mei Ju Luo, Dali Zhang, Jin ZHANG

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

This paper considers a class of stochastic second-order-cone complementarity problems (SSOCCP), which are generalizations of the noticeable stochastic complementarity problems and can be regarded as the Karush–Kuhn–Tucker conditions of some stochastic second-order-cone programming problems. Due to the existence of random variables, the SSOCCP may not have a common solution for almost every realization. In this paper, motivated by the works on stochastic complementarity problems, we present a deterministic formulation called the expected residual minimization formulation for SSOCCP. We present an approximation method based on the Monte Carlo approximation techniques and investigate some properties related to existence of solutions of the ERM formulation. Furthermore, we experiment some practical applications, which include a stochastic natural gas transmission problem and a stochastic optimal power flow problem in radial network.

Original languageEnglish
Pages (from-to)197-233
Number of pages37
JournalMathematical Programming
Volume165
Issue number1
DOIs
Publication statusPublished - 1 Sep 2017

Scopus Subject Areas

  • Software
  • Mathematics(all)

User-Defined Keywords

  • ERM formulation
  • Monte Carlo approximation
  • Natural gas transmission
  • Optimal power flow
  • SSOCCP

Fingerprint

Dive into the research topics of 'Stochastic second-order-cone complementarity problems: expected residual minimization formulation and its applications'. Together they form a unique fingerprint.

Cite this