节点文献
一种基于粒子群算法和Hopfield网络求解TSP问题的方法
Comparison on Solving TSP via Intelligent Algorithm
【摘要】 针对Hopfield网络求解TSP问题经常出现局部最优解,将粒子群算法(PSO)与Hopfield神经网络结合,提出一种基于粒子群的Hopfield神经网络方法。实验证实这种方法能够以更大概率收敛到全局最优。
【Abstract】 Since the Hopfield network solving traveling salesman problem often suffers from being trapped in local extrema,The particle swarm optimization(PSO) and Hopfield neural networks(HNN) are combined,and proposed a novel algorithm,PSO-HNN.Experiments showcase that the proposed method can converge on global extrema with a higher probability than Hopfield Solving TSP.
【关键词】 旅行商问题;
粒子群算法;
Hopfield网络;
【Key words】 traveling salesman problem particle swarm optimization Hopfield network;
【Key words】 traveling salesman problem particle swarm optimization Hopfield network;
【基金】 国家自然科学基金(60473065,60572063)资助
- 【文献出处】 科学技术与工程 ,Science Technology and Engineering , 编辑部邮箱 ,2009年08期
- 【分类号】TP183
- 【被引频次】2
- 【下载频次】272