首页> 外文会议>International Conference on Intelligent Data Engineering and Automated Learing(IDEAL 2007); 20071216-19; Birmingham(GB) >Hybrid Cross-Entropy Method/Hopfield Neural Network for Combinatorial Optimization Problems
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Hybrid Cross-Entropy Method/Hopfield Neural Network for Combinatorial Optimization Problems

机译:组合优化问题的混合交叉熵方法/ Hopfield神经网络

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摘要

This paper presents a novel hybrid algorithm for combinatorial optimization problems based on mixing the cross-entropy (CE) method and a Hopfield neural network. The algorithm uses the CE method as a global search procedure, whereas the Hopfield network is used to solve the constraints associated to the problems. We have shown the validity of our approach in several instance of the generalized frequency assignment problem.
机译:本文提出了一种新的混合算法,该算法基于混合交叉熵(CE)方法和Hopfield神经网络来解决组合优化问题。该算法将CE方法用作全局搜索过程,而Hopfield网络用于解决与问题相关的约束。我们已经在广义频率分配问题的几种情况下证明了我们方法的有效性。

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