计算机与现代化Issue(8)：204-208,5.DOI:10.3969/j.issn.1006-2475.2013.08.051
一种求解旅行商问题的LV回复式神经网络模型
A Lotka-Volterra Recurrent Neural Network Model for Solving TSP
摘要
Abstract
The traveling salesman problem (TSP) is a combinational optimization problem.Firstly,constructing an energy function to express the TSP,and a valid near optimization traveling path of TSP could be obtained at an energy minimum point of the energy function.After that,a Lotka-Volterra (LV) recurrent neural network (RNN) model is proposed to solve energy minimum points of the energy function.Experiments show that the proposed LV RNN model should converge to the energy minimum points of the corresponding energy function,and that compared with Hopfield network,the proposed LV RNN has better performance on solving TSP.关键词
Lotka-Volterra回复式神经网络/能量函数/旅行商问题/稳定吸引子/能量最小点Key words
Lotka-Volterra recurrent neural networks(LV RNNs) / energy function/ traveling salesman problem (TSP) / stable attractor/ energy minimum point分类
信息技术与安全科学引用本文复制引用
郑伯川..一种求解旅行商问题的LV回复式神经网络模型[J].计算机与现代化,2013,(8):204-208,5.基金项目
四川省教育厅重点项目(12ZA172) （12ZA172）
西华师范大学校项目(10A003,12B023) （10A003,12B023）
