A novel recurrent nonlinear neural network for solving quadratic programming problems
A novel recurrent nonlinear neural network for solving quadratic programming problems
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DOI：
10.1016/j.apm.2010.10.001
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发表时间：
2011-04
影响因子：
5
通讯作者：
S. Effati;M. Ranjbar
中科院分区：
文献类型：
--
作者：
S. Effati;M. Ranjbar
本文提出了一种新的求解二次规划问题的神经网络。新模型形式简单，计算量少，收敛速度快。它非常快地收敛到对偶问题的精确解，并通过代入一个公式，得到原问题的最优解。用一种数值方法求解神经网络模型。最后，简单的数值例子提供更多的说明。
This paper presents a new neural network for solving quadratic programming problems. The new model has a simple form, furthermore it has a good convergence rate with a less number calculation operation than the old models. It converges very fast to exact solution of the dual problem and by substituting in a formulation, the optimal solution of the original problem is obtained. Neural network model with one of numerical method is solved. Finally, simple numerical examples are provided for more illustration.