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Fixed-Point Iteration Method for Solving the Convex Quadratic Programming with Mixed Constraints
Department of Mathematics & Physics, Beijing Institute of Petrochemical Technology, Beijing, China
Department of Mathematics & Physics, Beijing Institute of Petrochemical Technology, Beijing, China
Department of Mathematics & Physics, Beijing Institute of Petrochemical Technology, Beijing, China
Department of Mathematics & Physics, Beijing Institute of Petrochemical Technology, Beijing, China
- 1 Department of Mathematics & Physics, Beijing Institute of Petrochemical Technology, Beijing, China
- 2 Department of Mathematics & Physics, Beijing Institute of Petrochemical Technology, Beijing, China
- 3 Department of Mathematics & Physics, Beijing Institute of Petrochemical Technology, Beijing, China
- 4 Department of Mathematics & Physics, Beijing Institute of Petrochemical Technology, Beijing, China
Applied Mathematics·Volume 05 (2014)·Pages 256–262·Published 17 January 2014·DOI10.4236/am.2014.52027
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Abstract
The present paper is devoted to a novel smoothing function method for convex quadratic programming problem with mixed constrains, which has important application in mechanics and engineering science. The problem is reformulated as a system of non - smooth equations, and then a smoothing function for the system of non - smooth equations is proposed. The condition of convergences of this iteration algorithm is given. Theory analysis and primary numerical results illustrate that this method is feasible and effective .
KeywordsFixed-Point IterationConvex Quadratic Programming ProblemConvergenceSmoothing Function
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