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基于Hopfield神经网络的单周期船舶调度模型及算法

Model & Algorithm of the Shipping Schedule Based on Single-cycle Hopfield Artificial Neural Network

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【作者】 谢小良符卓

【Author】 XIE Xiao-liang1,2, FU Zhuo1(1 School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China; 2 School of Information, Hunan University of Commerce, Changsha 410205, China)

【机构】 中南大学交通运输工程学院

【摘要】 从组合优化的角度介绍了基于Hopfield神经网络的单周期船舶调度问题的数学模型.建立了神经网络系统能量函数与优化问题目标函数之间的对应关系,提出了连续型Hopfield神经网络的解算方案,并通过实际算例表明该方法的有效性.

【Abstract】 From the point of the combination optimization view, we study model of single-cycle and algorithm for the shipping schedule though use of Hopfield artificial neural network. The corresponding relationships between neural network and optimal problem were built, such as neural network energy function and objective of optimal problem, and then a continuous Hopfield neural network (CHNN) is designed and applied to the processing. Finally, we give an application to demonstrate its effectiveness.

【基金】 国家自然科学基金项目(70671108);湖南省教育厅科研项目(08C470)
  • 【文献出处】 微电子学与计算机 ,Microelectronics & Computer , 编辑部邮箱 ,2008年10期
  • 【分类号】TP391.41
  • 【被引频次】14
  • 【下载频次】306
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