Vieira Frederico Carvalho, Dória Neto Adrião Duarte, Costa José Alfredo Ferreira
Computer Engineering Department, Universidade Federal do Rio Grande do Norte, Natal-RN, 59072-970, Brazil.
Int J Neural Syst. 2003 Apr;13(2):59-66. doi: 10.1142/S0129065703001443.
This paper presents an approach to the well-known Travelling Salesman Problem (TSP) using Self-Organizing Maps (SOM). The SOM algorithm has interesting topological information about its neurons configuration on cartesian space, which can be used to solve optimization problems. Aspects of initialization, parameters adaptation, and complexity analysis of the proposed SOM based algorithm are discussed. The results show an average deviation of 3.7% from the optimal tour length for a set of 12 TSP instances.
本文提出了一种使用自组织映射（SOM）解决著名旅行商问题（TSP）的方法。SOM算法在笛卡尔空间上关于其神经元配置具有有趣的拓扑信息，可用于解决优化问题。文中讨论了基于SOM的算法的初始化、参数自适应和复杂度分析等方面。结果表明，对于一组12个TSP实例，与最优巡回长度的平均偏差为3.7%。
