Araújo F, Ribeiro B, Rodrigues L
Faculdade de Ciências of Universidade de Lisboa, 1749-016 Lisboa, Portugal.
IEEE Trans Neural Netw. 2001;12(5):1067-73. doi: 10.1109/72.950136.
This paper presents a new neural network to solve the shortest path problem for inter-network routing. The proposed solution extends the traditional single-layer recurrent Hopfield architecture introducing a two-layer architecture that automatically guarantees an entire set of constraints held by any valid solution to the shortest path problem. This new method addresses some of the limitations of previous solutions, in particular the lack of reliability in what concerns successful and valid convergence. Experimental results show that an improvement in successful convergence can be achieved in certain classes of graphs. Additionally, computation performance is also improved at the expense of slightly worse results.
本文提出了一种新的神经网络，用于解决网络间路由的最短路径问题。所提出的解决方案扩展了传统的单层递归霍普菲尔德架构，引入了一种双层架构，该架构自动保证了最短路径问题的任何有效解决方案所具有的一整套约束条件。这种新方法解决了先前解决方案的一些局限性，特别是在成功和有效收敛方面缺乏可靠性的问题。实验结果表明，在某些类型的图中可以实现成功收敛的改进。此外，计算性能也得到了提高，代价是结果略有变差。
