A projected-based neural network method for second-order cone programming

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Abstract

A projected-based neural network method for second-order cone programming is proposed. The second-order cone programming is transformed into an equivalent projection equation. The projection on the second-order cone is simple and costs less computation time. We prove that the proposed neural network is stable in the sense of Lyapunov and converges to an exact solution of the second-order cone programming problem. The simulation experiments show our method is an efficient method for second-order cone programming problems.

Keywords

Second-order cone programming Projection equation Neural network method Primal-dual interior point method 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.School of Computer ScienceXi’an Science and Technology UniversityXi’anChina
  2. 2.School of Mathematics and StatisticsXidian UniversityXi’anChina

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