Robust weighted expected residual minimization formulation for stochastic vector variational inequalities

Yong Zhao, Zai Yun Peng, Yun-Bin Zhao

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Abstract

In order to deal with (stochastic) multi-objective optimization problems, a robust Pareto optimal solution by minimizing the worst case weighted sum of objectives on a given weight set is considered [31,32]. Based on this idea, we introduce a new class of deterministic model for stochastic vector variational inequalities, called robust weighted expected residual minimization model. We then propose sample average approximation (SAA) approach to solve robust weighted expected
residual minimization problems. Some convergence results are established for the approximation problem in terms of the optimal value and the set of optimal solutions.
Original languageEnglish
Pages (from-to)5825-5833
JournalJournal of Nonlinear Science and Applications
Volume10
Issue number11
DOIs
Publication statusPublished - 17 Nov 2017

Keywords

  • Robust weighted expected residual minimization
  • stochastic vector variational inequalities
  • convergence

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