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一种改进的自组织映射算法求解旅行商问题 被引量:2

An Improved Self-organizing Algorithm for Solving the Traveling Salesman Problem
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摘要 目前,没有求解旅行商问题的非常有效的方法。提出了一种求解该问题的LNSOM算法,在自组织映射算法的基础上,改进了学习率和邻域函数变量。利用matlab 2011软件进行求解,其中5个旅行商问题实例的结果优于MSTSP和SETSP算法,另外,10个实例的平均误差为1.445 6%。实验结果表明,新算法的误差更小,并保持了SOM算法较低的计算复杂度。 There are no ellective corresponding solutions to the traveling salesman problems (TSP). To address the problems, a new algorithm by improving learning rate and neighborhood function variance of the self-organizing map (SOM) is presented. The solutions of five instances are better than MSTSP and SETSP in matlab2011. The average error is only 1.445 6 % of anthor ten. The new algorithm has the advantage of smaller error and maintaining low SOM algorithm computational complexity.
出处 《上海第二工业大学学报》 2012年第1期48-52,共5页 Journal of Shanghai Polytechnic University
基金 河北省软科学计划项目(No.104572108) 河北农业大学非生命课题(No.FS201008) 保定市科学技术研究与发展指导计划软科学项目(No.11ZR004)
关键词 镁合金 表面特性 TiO2薄膜:磁控溅射 traveling salesman problem self-organizing map learning rate neighborhood function variance
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