Neural Network for Solving SOCQP and SOCCVI Based on Two Discrete-Type Classes of SOC Complementarity Functions

Juhe Sun, Xiao Ren Wu, B. Saheya, Jein Shan Chen, Chun Hsu Ko

Research output: Contribution to journalArticle

Abstract

This paper focuses on solving the quadratic programming problems with second-order cone constraints (SOCQP) and the second-order cone constrained variational inequality (SOCCVI) by using the neural network. More specifically, a neural network model based on two discrete-type families of SOC complementarity functions associated with second-order cone is proposed to deal with the Karush-Kuhn-Tucker (KKT) conditions of SOCQP and SOCCVI. The two discrete-type SOC complementarity functions are newly explored. The neural network uses the two discrete-type families of SOC complementarity functions to achieve two unconstrained minimizations which are the merit functions of the Karuch-Kuhn-Tucker equations for SOCQP and SOCCVI. We show that the merit functions for SOCQP and SOCCVI are Lyapunov functions and this neural network is asymptotically stable. The main contribution of this paper lies on its simulation part because we observe a different numerical performance from the existing one. In other words, for our two target problems, more effective SOC complementarity functions, which work well along with the proposed neural network, are discovered.

Original languageEnglish
Article number4545064
JournalMathematical Problems in Engineering
Volume2019
DOIs
Publication statusPublished - 2019 Jan 1

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Second-order Cone
Complementarity
Variational Inequalities
Cones
Neural Networks
Neural networks
Merit Function
Cone Constraints
Karush-Kuhn-Tucker Conditions
Unconstrained Minimization
Quadratic programming
Lyapunov functions
Asymptotically Stable
Quadratic Programming
Neural Network Model
Lyapunov Function
Class
Model-based
Target
Simulation

ASJC Scopus subject areas

  • Mathematics(all)
  • Engineering(all)

Cite this

Neural Network for Solving SOCQP and SOCCVI Based on Two Discrete-Type Classes of SOC Complementarity Functions. / Sun, Juhe; Wu, Xiao Ren; Saheya, B.; Chen, Jein Shan; Ko, Chun Hsu.

In: Mathematical Problems in Engineering, Vol. 2019, 4545064, 01.01.2019.

Research output: Contribution to journalArticle

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