| LT递归神经网络求解旅行商问题研究 |
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| 引用本文： | 周伟,蒲晓蓉,屈鸿.LT递归神经网络求解旅行商问题研究[J].电子科技大学学报（自然科学版）,2011,40(4):592-595. |
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| 作者姓名： | 周伟 蒲晓蓉 屈鸿 |
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| 作者单位： | 1.西南民族大学计算机科学与技术学院 成都 610041; |
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| 基金项目： | 国家自然科学基金(60973070）;教育部博士点基金(200806141049) |
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| 摘 要： | 提出了一种基于LT递归神经网络的旅行商问题求解方法.采用离散型神经网络模型,先给出模型有界性和完全收敛性的证明,再给出保证网络的稳定输出解为旅行商问题有效路径的条件.在此基础上结合局部最小值逃选方法获得较优的路径.在与基于LV递归神经网络的算法比较实验证明,该算法在总体上能获得更好的有效路径.
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| 关 键 词： | 智能计算 递归神经网络 系统稳定性 旅行商问题 |
| 收稿时间： | 2009-06-25 |
Discrete-Time Recurrent Neural Networks with Linear Threshold Neurons for Solving Traveling Salesman Problem |
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| Affiliation: | 1.Collage of Computer Science and Technology,Southwest University of Nationalities Chengdu 610041;2.School of Computer Science and Engineering,University of Electronic Science Technology of China Chengdu 610054 |
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| Abstract: | This paper discusses a class of discrete-time recurrent neural networks with linear threshold (LT) neurons for solving traveling salesman problem (TSP). It first addresses the boundedness and complete stability，then gives a theorem to ensure all the networks' iteration solutions to be valid solutions. We also present an algorithm based on such networks with a local escape way. Simulation results illustrate the developed method. Compared with the TSP solutions done by Lotka-Volterra (LV) neural networks, the presented method has better performance. |
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