s of Mixed Complementarity Problems

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DOI: 10.4236/jamp.2020.81002    120 Downloads   263 Views
Peng Zhang, Zhensheng Yu


College of Science, University of Shanghai for Science and Technology, Shanghai, China.


In this paper, we consider an extragradient thresholding algorithm for finding the sparse solution of mixed complementarity problems (MCPs). We establish a relaxation l1 regularized projection minimization model for the original problem and design an extragradient thresholding algorithm (ETA) to solve the regularized model. Furthermore, we prove that any cluster point of the sequence generated by ETA is a solution of MCP. Finally, numerical experiments show that the ETA algorithm can effectively solve the l1 regularized projection minimization model and obtain the sparse solution of the mixed complementarity problem.


Mixed Complementarity Problem, Sparse Solution, l1 Regularized Projection Minimization Model, Extragradient Thresholding Algorithm

Cite this paper

Zhang, P. and Yu, Z. (2020) Sparse Solutions of Mixed Complementarity Problems. Journal of Applied Mathematics and Physics, 8, 10-22. doi: 10.4236/jamp.2020.81002.
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