随机网络的α最短路径问题

Study on the α-shortest Path Problem of Stochastic Network

为了求解随机网络中满足置信度为α的最短路径问题,提出了一种BP神经网络遗传算法。首先给出了随机网络的定义,建立了α最短路径模型;然后采用BP神经网络拟合非线性函数,遗传算法优化BP神经网络输出的方法求解该问题。实验结果表明,提出的模型和算法能有效求解随机网络的α最短路径问题。

In order to solve the shortest path problem of stochastic network to meet the confidence level of α, a genetic algo-rithm of BP neural network was proposed to address the α-shortest path problem of a stochastic network. In this paper, the definitionof stochastic network was given and the α-shortest path model was established. The nonlinear function fit BP neural network for theproblem and then the output of BP neural network was optimized by genetic algorithm. The simulation experiment shows that the pro-posed model and algorithm can effectively solve the α?shortest path problem of the stochastic network.