Result: A Self-Adaptive Technique for Solving Variational Inequalities: A New Approach to the Problem
Title:
A Self-Adaptive Technique for Solving Variational Inequalities: A New Approach to the Problem
Source:
Journal of Function Spaces, Vol 2022 (2022)
Publisher Information:
Wiley, 2022.
Publication Year:
2022
Subject Terms:
Economics, Fixed-Point Problems, Mathematical analysis, Quantum mechanics, 01 natural sciences, Engineering, Interior-Point Methods, Field (mathematics), QA1-939, FOS: Mathematics, 0101 mathematics, Economic growth, Civil and Structural Engineering, Scheme (mathematics), Variational inequality, Interpretation (philosophy), Numerical Analysis, Numerical Optimization Techniques, Extension (predicate logic), Physics, Mathematical optimization, Topology Optimization in Structural Engineering, Pure mathematics, Iterative Algorithms for Nonlinear Operators and Optimization, Applied mathematics, Computer science, Programming language, Computational Theory and Mathematics, Computer Science, Physical Sciences, Convergence (economics), Nonlinear system, Mathematics, Mixed-Integer Nonlinear Programs
Document Type:
Academic journal
Article<br />Other literature type
File Description:
text/xhtml
Language:
English
ISSN:
2314-8888
2314-8896
2314-8896
DOI:
10.1155/2022/7078707
DOI:
10.60692/xxejv-cry11
DOI:
10.60692/b8pw7-a5v16
Rights:
CC BY
Accession Number:
edsair.doi.dedup.....7444b62844cfd12c7b9e70d0801968c7
Database:
OpenAIRE
Further Information
Variational inequalities are considered the most significant field in applied mathematics and optimization because of their massive and vast applications. The current study proposed a novel iterative scheme developed through a fixed-point scheme and formulation for solving variational inequalities. Modification is done by using the self-adaptive technique that provides the basis for predicting a new predictor-corrector self-adaptive for solving nonlinear variational inequalities. The motivation of the presented study is to provide a meaningful extension to existing knowledge through convergence at mild conditions. The numerical interpretation provided a significant boost to the results.