%0 Journal Article
%T An Algorithm for Solving a Multi-city Traveling Salesman Problem Based on Learning of Hopfield Network<br>基于Hopfield网络学习的多城市旅行商问题的解法
%A JIN Haihe
%A CHEN Jian
%A TANG Zheng
%A ZHENG Guoqi
%A <br>金海和
%A 陈剑
%A 唐政
%A 郑国旗
%J 系统工程理论与实践
%D 2003
%I 
%X This paper proposes an algorithm of solving the multi-city traveling salesman problem based on Hopfield network learning. The algorithm uses the Hopfield network learning as basal arithmetic operators, to look for the optimal or better solution by dividing up, calculation and linking the group of cities with the given rules. The algorithm is applied to a 100-city traveling salesman problem, and its effectiveness is confirmed by simulation. This algorithm is free from limitation of the city number; and speedup can be implemented by parallel operation; and hardware can be achieved easily because of simplicity and clarity in algorithm.
%K Hopfield neural network learning
%K learning arithmetic operators
%K combinatorial optimization problem
%K local minimum problem
%K multi-city traveling salesman problem<br>Hopfield神经网络学习
%K 学习算子
%K 组合优化问题
%K 极小值问题
%K 多城市旅行商问题
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=01BA20E8BA813E1908F3698710BBFEFEE816345F465FEBA5&cid=962324E222C1AC1D&jid=1D057D9E7CAD6BEE9FA97306E08E48D3&aid=369DE16041D1FF57&yid=D43C4A19B2EE3C0A&vid=EA389574707BDED3&iid=DF92D298D3FF1E6E&sid=8C83C265AD318E34&eid=03F1579EF92A5A32&journal_id=1000-6788&journal_name=系统工程理论与实践&referenced_num=1&reference_num=9