Variational Inequality Problem: Theory, Analysis and Applications
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E: Applied Mathematics".
Deadline for manuscript submissions: 31 March 2026 | Viewed by 29
Special Issue Editor
Interests: variational inequalities; fixed-point theory; minimax problems; optimization problems; variational inclusions; predict methods in statistics; prediction by applied mathematical algorithms; machine learnings; artificial intelligence; predict algorithms with applications in health care including heart disease
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Variational inequalities introduced in the early sixties have witnessed explosive growth in theoretical advances, algorithmic development and applications across all disciplines of pure and applied sciences. They combine novel theoretical and algorithmic advances with new application domains. Analysis of these problems requires a blend of techniques from convex analysis, functional analysis and numerical analysis. As a result of the interactions between different branches of mathematics, statistics and engineering sciences, a variety of techniques are suggested for the analysis of various algorithms for solving variational inequalities and related optimization problems. These include minimax problems, which may be extended to the study of artificial intelligence with machine learnings. Meanwhile, variational inclusions are useful and important extensions and generalizations of variational inequalities with a wide range of applications in industry, mathematical finance, economics, decision sciences, ecology, mathematics and engineering sciences.
We invite researchers original research and comprehensive review articles that will stimulate the continuing efforts to numerical analysis for variational inequality problems and fixed-point problems with applications.
Potential topics of interest include, but are not limited to:
- Numerical methods for (general) variational inequalities and inclusions, nonlinear equations, fixed-point problems, and systems of variational inequalities and inclusions;
- Split feasibility problems;
- Common problems associated with variational inequalities and fixed-point problems;
- Proximal-point algorithms;
- Numerical comparisons;
- Stability of numerical methods;
- Variational inequalities;
- Fixed-point theory;
- Minimax problems;
- Optimization problems;
- Variational inclusions;
- Prediction methods in statistics;
- Prediction algorithms by applied mathematical algorithms;
- Machine learning;
- Artificial intelligence;
- Prediction algorithms with applications in health care including heart disease.
Prof. Dr. Zhenyu Huang
Guest Editor
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Keywords
- variational inequalities
- fixed-point theory
- minimax problems
- optimization problems
- variational inclusions
- prediction methods in statistics
- prediction algorithms in applied mathematics
- machine learning
- artificial intelligence
- prediction algorithms with applications in health care, including heart disease
- common problems associated with variational inequalities and fixed-point problems
- proximal-point algorithms
- numerical comparisons
- stability of numerical methods
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