Numerical solution for linear and quadratic programming problems using a recurrent neural network

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摘要

A recurrent neural network, is proposed in this paper for solving linear and quadratic programming problems. The main advantage of this network is that here we are not in need of parameters setting. Moreover, using this network we can solve primal programming problems and their duals simultaneously. We prove the global convergence of the neural network and demonstrate the advanced performance of the proposed network by means of simulation of several numerical examples.

论文关键词:Linear and quadratic programming,Neural networks,Dynamical systems

论文评审过程:Available online 16 March 2007.

论文官网地址:https://doi.org/10.1016/j.amc.2007.02.149