摘要
利用神经网络求解组合优化问题,是一种有效的途径。对连续Hopfield网络的数学模型及稳定性进行了分析;探讨了组合优化问题的神经网络求解方法,针对传统方法参数配置复杂、收敛速度慢等不足,提出了改进算法;最后,通过系统仿真与性能测试验证了该算法的可行性。
Using neural networks to solve combinatorial optimization problems is an effective approach.Analyzes the mathematical model and stability of continuous Hopfield neural network,discusses the use of CHNN to solve combinatorial optimization problem and puts forward the improved algorithm aiming at the insufficiency of the traditional method of parameters configuration complex and convergence rate slower.Finally,through the system simulation and performance testing,demonstrates the algorithm feasible.
出处
《湖南工业大学学报》
2011年第3期42-46,共5页
Journal of Hunan University of Technology
关键词
组合优化
神经网络
连续HOPFIELD网络
旅行商问题
combinatorial optimization
neural network
continuous hopfield neural network
traveling salesman problem