Fixed-Point Iteration Method for Solving the Convex Quadratic Programming with Mixed Constraints - Applied Mathematics

AM > Vol.5 No.2, January 2014

Applied Mathematics

Volume 5, Issue 2 (January 2014)

ISSN Print: 2152-7385 ISSN Online: 2152-7393

Google-based Impact Factor: 0.58 Citations

Fixed-Point Iteration Method for Solving the Convex Quadratic Programming with Mixed Constraints ()

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DOI: 10.4236/am.2014.52027 4,429 Downloads 6,896 Views Citations

Author(s)

Ruopeng Wang, Hong Shi, Kai Ruan, Xiangyu Gao

Affiliation(s)

Department of Mathematics & Physics, Beijing Institute of Petrochemical Technology, Beijing, China.

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.

KEYWORDS

Fixed-Point Iteration; Convex Quadratic Programming Problem; Convergence; Smoothing Function

Share and Cite:

Wang, R. , Shi, H. , Ruan, K. and Gao, X. (2014) Fixed-Point Iteration Method for Solving the Convex Quadratic Programming with Mixed Constraints. Applied Mathematics, 5, 256-262. doi: 10.4236/am.2014.52027.

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