Generalized nonlinear mixed quasi-variational inequalities

By Nan-Jing Huang, M. Bai, Yeol Je Cho, Shin Min Kang. 2000

53 citations recorded by the source corpus.

Abstract In this paper, we introduce and study a new class of quasi-variational inequalities, which is called the generalized nonlinear set-valued mixed quasi-variational inequality. Using the resolvent operator technique for maximal monotone mapping, we construct some new iterative algorithms for solving this class of generalized nonlinear set-valued mixed quasi-variational inequalities. We prove the existence of solution for this kind of generalized nonlinear set-valued mixed quasivariational inequalities without compactness and the convergence of iterative sequences generated by the algorithms. We also discuss the convergence and stability of perturbed iterative algorithm for solving a class of generalized nonlinear mixed quasi-variational inequalities.

Subfields: Civil and Structural Engineering, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/245fcdaea34413241c15d48ce0ff46360659a75c

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In Computational Theory and Mathematics

1. Jianzhon Zhang
2. N. Xiu
3. Muhammad Aslam Noor

Citations in the corpus

• Some recent advances in projection-type methods for variational inequalities (2003, background): “The interested readers may consult the survey by Noor [81,82], the papers [1,18,48,63,80,83–87,116,122,124], and the references therein.”