NEW THREE-STEP ITERATIVE METHOD FOR SOLVING MIXED VARIATIONAL INEQUALITIES

2011 ◽  
Vol 08 (01) ◽  
pp. 139-150
Author(s):  
ABDELLAH BNOUHACHEM ◽  
MUHAMMAD ASLAM NOOR ◽  
ZHAOHAN SHENG ◽  
EISA AL-SAID
Keyword(s):  
Iterative Method ◽  
Variational Inequalities ◽  
Numerical Experiments ◽  
New Method ◽  
Descent Direction ◽  
Mild Conditions ◽  
Globally Convergent ◽  
Special Cases ◽  
Mixed Variational Inequalities

In this paper, we suggest and analyze a new three-step iterative method for solving mixed variational inequalities. The new iterate is obtained by using a descent direction. We prove that the new method is globally convergent under suitable mild conditions. Our results can be viewed as significant extensions of the previously known results for mixed variational inequalities. Since mixed variational inequalities include variational inequalities as special cases, our method appears to be a new one for solving variational inequalities. Preliminary numerical experiments are included to illustrate the advantage and efficiency of the proposed method.

THREE-STEP PROJECTION METHOD FOR GENERAL VARIATIONAL INEQUALITIES

2012 ◽  
Vol 26 (13) ◽  
pp. 1250066 ◽  
Author(s):  
ABDELLAH BNOUHACHEM ◽  
MUHAMMAD ASLAM NOOR
Keyword(s):  
Variational Inequalities ◽  
Projection Method ◽  
New Method ◽  
Descent Direction ◽  
Mild Conditions ◽  
Globally Convergent ◽  
General Variational Inequalities ◽  
Iterative Projection Method

In this paper, we suggest and analyze a new three-step iterative projection method for solving general variational inequalities in conjunction with a descent direction. We prove that the new method is globally convergent under suitable mild conditions. An example is given to illustrate the advantage and efficiency of the proposed method.

scholarly journals Solving Mixed Variational Inequalities Beyond Convexity

2021 ◽  
Author(s):  
Sorin-Mihai Grad ◽  
Felipe Lara
Keyword(s):  
Iterative Method ◽  
Variational Inequalities ◽  
Numerical Experiments ◽  
Golden Ratio ◽  
Mixed Variational Inequalities

AbstractWe show that Malitsky’s recent Golden Ratio Algorithm for solving convex mixed variational inequalities can be employed in a certain nonconvex framework as well, making it probably the first iterative method in the literature for solving generalized convex mixed variational inequalities, and illustrate this result by numerical experiments.

scholarly journals Three-step iterations for mixed quasi variational-like inequalities

2005 ◽  
Vol 2005 (14) ◽  
pp. 2299-2306
Author(s):  
Muhammad Aslam Noor
Keyword(s):  
Variational Inequalities ◽  
Optimization Problems ◽  
New Method ◽  
Convergence Criteria ◽  
Auxiliary Principle ◽  
Auxiliary Principle Technique ◽  
Mild Conditions ◽  
Special Cases ◽  
Bregman Function ◽  
Predictor Corrector

In this paper, we use the auxiliary principle technique in conjunction with the Bregman function to suggest and analyze a three-step predictor-corrector method for solving mixed quasi variational-like inequalities. We also study the convergence criteria of this new method under some mild conditions. As special cases, we obtain various new and known methods for solving variational inequalities and related optimization problems.

scholarly journals A Self-Adaptive Method for Solving a System of Nonlinear Variational Inequalities

2007 ◽  
Vol 2007 ◽  
pp. 1-7
Author(s):  
Chaofeng Shi
Keyword(s):  
Iterative Method ◽  
Variational Inequalities ◽  
Adaptive Method ◽  
New Method ◽  
Computational Results ◽  
Computation Cost ◽  
Self Adaptive

The system of nonlinear variational inequalities (SNVI) is a useful generalization of variational inequalities. Verma (2001) suggested and analyzed an iterative method for solving SNVI. In this paper, we present a new self-adaptive method, whose computation cost is less than that of Verma's method. The convergence of the new method is proved under the same assumptions as Verma's method. Some preliminary computational results are given to illustrate the efficiency of the proposed method.

scholarly journals Some Proximal Methods for Solving Mixed Variational Inequalities

2012 ◽  
Vol 2012 ◽  
pp. 1-9
Author(s):  
Muhammad Aslam Noor ◽  
Zhenyu Huang
Keyword(s):  
Variational Inequalities ◽  
Extragradient Method ◽  
Fixed Point Problem ◽  
Point Problem ◽  
Proximal Methods ◽  
Proximal Point ◽  
Equivalent Formulation ◽  
New Methods ◽  
Special Cases ◽  
Mixed Variational Inequalities

It is well known that the mixed variational inequalities are equivalent to the fixed point problem. We use this alternative equivalent formulation to suggest some new proximal point methods for solving the mixed variational inequalities. These new methods include the explicit, the implicit, and the extragradient method as special cases. The convergence analysis of these new methods is considered under some suitable conditions. Our method of constructing these iterative methods is very simple. Results proved in this paper may stimulate further research in this direction.

scholarly journals Parametric Extended General Mixed Variational Inequalities

2012 ◽  
Vol 2012 ◽  
pp. 1-11
Author(s):  
Muhammad Aslam Noor
Keyword(s):  
Variational Inequalities ◽  
Complementarity Problems ◽  
Equivalent Formulation ◽  
Resolvent Equations ◽  
Special Cases ◽  
General Variational Inequalities ◽  
Significant Extension ◽  
Mixed Variational Inequalities ◽  
The Given

It is well known that the resolvent equations are equivalent to the extended general mixed variational inequalities. We use this alternative equivalent formulation to study the sensitivity of the extended general mixed variational inequalities without assuming the differentiability of the given data. Since the extended general mixed variational inequalities include extended general variational inequalities, quasi (mixed) variational inequalities and complementarity problems as special cases, results obtained in this paper continue to hold for these problems. In fact, our results can be considered as a significant extension of previously known results.

scholarly journals An Improved Two-Step Method for Generalized Variational Inequalities

2013 ◽  
Vol 2013 ◽  
pp. 1-8
Author(s):  
Haibin Chen
Keyword(s):  
Variational Inequalities ◽  
Error Bound ◽  
Point Of View ◽  
Large Decrease ◽  
Step Method ◽  
Generalized Variational Inequalities ◽  
Mild Conditions ◽  
Extragradient Algorithm ◽  
Globally Convergent ◽  
Geometric Point

We propose an improved two-step extragradient algorithm for pseudomonotone generalized variational inequalities. It requires two projections at each iteration and allows one to take different stepsize rules. Moreover, from a geometric point of view, it is shown that the new method has a long stepsize, and it guarantees that the distance from the next iterative point to the solution set has a large decrease. Under mild conditions, we show that the method is globally convergent, and then the R-linearly convergent property of the method is proven if a projection-type error bound holds locally.

scholarly journals Explicit Iterative Method for Variational Inequalities on Hadamard Manifolds

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Muhammad Aslam Noor ◽  
Khalida Inayat Noor
Keyword(s):  
Iterative Method ◽  
Variational Inequalities ◽  
New Method ◽  
Hadamard Manifold ◽  
Hadamard Manifolds ◽  
Auxiliary Principle ◽  
Auxiliary Principle Technique ◽  
Monotonicity Results

An explicit iterative method for solving the variational inequalities on Hadamard manifold is suggested and analyzed using the auxiliary principle technique. The convergence of this new method requires only the partially relaxed strongly monotonicity, which is a weaker condition than monotonicity. Results can be viewed as refinement and improvement of previously known results.

scholarly journals Iterative resolvent methods for general mixed variational inequalities

2003 ◽  
Vol 16 (3) ◽  
pp. 283-294
Author(s):  
Muhammad Aslam Noor ◽  
Khalida Inayat Noor
Keyword(s):  
Variational Inequalities ◽  
Complementarity Problems ◽  
Splitting Methods ◽  
Pseudomonotone Operators ◽  
Special Cases ◽  
Mixed Variational Inequalities ◽  
Proof Of Convergence ◽  
Self Adaptive

In this paper, we use the technique of updating the solution to suggest and analyze a class of new self-adaptive splitting methods for solving general mixed variational inequalities. It is shown that these modified methods converge for pseudomonotone operators, which is a weaker condition than monotonicity. Proof of convergence is very simple. Since general mixed variational include variational inequalities and complementarity problems as special cases, our results continue to hold for these problems.

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