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Splitting Algorithms for General Pseudomonotone Mixed Variational Inequalities

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Abstract

In this paper, we suggest and analyze a number of resolvent-splitting algorithms for solving general mixed variational inequalities by using the updating technique of the solution. The convergence of these new methods requires either monotonicity or pseudomonotonicity of the operator. Proof of convergence is very simple. Our new methods differ from the existing splitting methods for solving variational inequalities and complementarity problems. The new results are versatile and are easy to implement.

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Authors and Affiliations

  1. Department of Mathematics and Statistics, Dalhousie University, Halifax, Nova Scotia, Canada

    MUHAMMAD ASLAM NOOR

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  1. MUHAMMAD ASLAM NOOR
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NOOR, M.A. Splitting Algorithms for General Pseudomonotone Mixed Variational Inequalities. Journal of Global Optimization 18, 75–89 (2000). https://doi.org/10.1023/A:1008322118873

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