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A Neural Network Approach for Nonlinear Bilevel Programming Problem

机译:非线性双层规划问题的神经网络方法

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摘要

A novel neural network approach is presented for solving nonlinear bilevel programming problem. The proposed neural network is proved to be Lya-punov stable and capable of generating optimal so-lution to the nonlinear bilevel programming prob-lem. The asymptotic properties of the neural net-work are analyzed and the condition for asymptotic stability, solution feasibility and solution optimality are derived. The transient behavior of the neural network is simulated and the validity of the network is verified with numerical examples.
机译:提出了一种解决非线性双层规划问题的新型神经网络方法。所提出的神经网络被证明是Lya-punov稳定的,并且能够为非线性双层规划问题生成最优解。分析了神经网络的渐近性质,推导了渐近稳定性的条件,解的可行性和解的最优性。仿真了神经网络的瞬态行为,并通过数值例子验证了网络的有效性。

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