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<p>The main objective of this paper is to introduce a kind of extended vertical stochastic <InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10957_2025_2811_Article_IEq3.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="20" /> </InlineMediaObject> <EquationSource Format="TEX">\(R_0\)</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi>R</mi> <mn>0</mn> </msub> </math></EquationSource> </InlineEquation>-tensor complementarity problems. We consider the sample average approximation (SAA) method to solve this proposed problem and prove the boundedness of the solution set. Then, we use the unconstrained optimization method to solve the transformed extended vertical stochastic <InlineEquation ID="IEq4"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10957_2025_2811_Article_IEq4.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="20" /> </InlineMediaObject> <EquationSource Format="TEX">\(R_{0}\)</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi>R</mi> <mn>0</mn> </msub> </math></EquationSource> </InlineEquation>-tensor complementarity problem. Finally, numerical results are presented.</p>

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Extended Vertical Stochastic \(\varvec{R}_{0}\)-Tensor Complementarity Problem

  • 期刊论文

  • 发表日期：

    2025年8月13日

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  • Shouqiang Du,
  • Duan Song,
  • Guangxuan Lin,
  • Yimin Wei

摘要

The main objective of this paper is to introduce a kind of extended vertical stochastic \(R_0\) R 0 -tensor complementarity problems. We consider the sample average approximation (SAA) method to solve this proposed problem and prove the boundedness of the solution set. Then, we use the unconstrained optimization method to solve the transformed extended vertical stochastic \(R_{0}\) R 0 -tensor complementarity problem. Finally, numerical results are presented.