求解旅行商问题的神经网络比较

B. F. J. La Maire, V. Mladenov
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引用次数: 23

摘要

TSP的任务是找到一条穿越多个城市的最短路径。这个看似简单的问题很难解决,因为可能的解决方案太多了。这就是为什么通常使用在合理时间内给出良好次优解的方法。本文比较了整数线性规划法、Hopfield神经网络和Kohonen自组织特征映射神经网络这三种方法的解的质量和找到正确参数的难易程度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of neural networks for solving the travelling salesman problem
The TSP deals with finding a shortest path through a number of cities. This seemingly simple problem is hard to solve because of the amount of possible solutions. Which is why methods that give a good suboptimal solution in a reasonable time are generally used. In this paper three methods were compared with respect to quality of solution and ease of finding correct parameters: the Integer Linear Programming method, the Hopfield Neural Network, and the Kohonen Self Organizing Feature Map Neural Network.
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