中文摘要：

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逸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。

英文摘要：

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.