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A neural network approach for solving linear bilevel programming problem

机译:解决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 proposed for solving linear bilevel programming problem. The proposed neural network is proved to be Lyapunov stable and capable of generating optimal solution to the linear bilevel programming problem. The numerical result shows that the neural network approach is feasible and efficient.
机译:提出了一种新颖的神经网络方法来解决线性双层规划问题。所提出的神经网络被证明是Lyapunov稳定的,并且能够为线性双层规划问题生成最优解。数值结果表明,神经网络方法是可行和有效的。

著录项

  • 来源
    《Knowledge-Based Systems》 |2010年第3期|239-242|共4页
  • 作者单位

    State Key Laboratory of Water Resource and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China;

    State Key Laboratory of Water Resource and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China;

    State Key Laboratory of Water Resource and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China;

    School of Information and Mathematics, Yangtze University, Jingzhou 434023, China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    linear bilevel programming; neural network; asymptotic stability; optimal solution;

    机译:线性双层编程;神经网络;渐近稳定性最佳解决方案;

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