View in EDS

Proximal-Type Algorithms for Solving Nonconvex Mixed Multivalued Quasi-Variational Inequality Problems.

Saved in:
Bibliographic Details
Title: Proximal-Type Algorithms for Solving Nonconvex Mixed Multivalued Quasi-Variational Inequality Problems.
Authors: Grad, S.-M.1 (AUTHOR) sorin-mihai.grad@ensta.fr, Muu, L.  D.2 (AUTHOR) ldmuu@math.ac.vn, Thang, T.  V.3 (AUTHOR) thangtv@epu.edu.vn
Source: Journal of Optimization Theory & Applications. Aug2025, Vol. 206 Issue 2, p1-26. 26p.
Abstract: We propose iterative algorithms of proximal point type for solving two classes of mixed multivalued quasi-variational inequality problems in real Euclidean spaces involving nonconvex functions, for which no similar algorithms are currently known. Our proposed algorithms combine the proximal type algorithm for solving mixed variational inequalities in a nonconvex framework, the Mann iteration scheme for approximating a fixed point of certain generalized nonexpansive multivalued mappings with the infeasible projection and cutting plane techniques for variational inequalities to generate iterative sequences that converge to a solution of a mixed multivalued quasi-variational inequality problem under mild assumptions. An application to generalized Nash (quasi)equilibrium problems is discussed. Numerical experiments confirm the usability of the introduced algorithms. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Optimization Theory & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 185849568
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Proximal-Type Algorithms for Solving Nonconvex Mixed Multivalued Quasi-Variational Inequality Problems.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Grad%2C+S%2E-M%2E%22">Grad, S.-M.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> sorin-mihai.grad@ensta.fr</i><br /><searchLink fieldCode="AR" term="%22Muu%2C+L%2E +D%2E%22">Muu, L.  D.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> ldmuu@math.ac.vn</i><br /><searchLink fieldCode="AR" term="%22Thang%2C+T%2E +V%2E%22">Thang, T.  V.</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> thangtv@epu.edu.vn</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Journal+of+Optimization+Theory+%26+Applications%22">Journal of Optimization Theory & Applications</searchLink>. Aug2025, Vol. 206 Issue 2, p1-26. 26p.
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: We propose iterative algorithms of proximal point type for solving two classes of mixed multivalued quasi-variational inequality problems in real Euclidean spaces involving nonconvex functions, for which no similar algorithms are currently known. Our proposed algorithms combine the proximal type algorithm for solving mixed variational inequalities in a nonconvex framework, the Mann iteration scheme for approximating a fixed point of certain generalized nonexpansive multivalued mappings with the infeasible projection and cutting plane techniques for variational inequalities to generate iterative sequences that converge to a solution of a mixed multivalued quasi-variational inequality problem under mild assumptions. An application to generalized Nash (quasi)equilibrium problems is discussed. Numerical experiments confirm the usability of the introduced algorithms. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Optimization Theory & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=185849568
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1007/s10957-025-02733-1
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 26
        StartPage: 1
    Titles:
      – TitleFull: Proximal-Type Algorithms for Solving Nonconvex Mixed Multivalued Quasi-Variational Inequality Problems.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Grad, S.-M.
      – PersonEntity:
          Name:
            NameFull: Muu, L.  D.
      – PersonEntity:
          Name:
            NameFull: Thang, T.  V.
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 08
              Text: Aug2025
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 00223239
          Numbering:
            – Type: volume
              Value: 206
            – Type: issue
              Value: 2
          Titles:
            – TitleFull: Journal of Optimization Theory & Applications
              Type: main
ResultId 1