随机交通网络约束最可靠路径问题

Constrained Reliable Shortest Path Problem in Stochastic Traffic Network

为了模拟仿真交通网络中,约束条件下考虑风险性车辆路径选择行为,建立随机交通网络环境下约束最可靠路径问题数学规划模型,并讨论了其对偶问题.采用梯度下降算法求解对偶问题,获得原问题最优值的上界和下界,通过迭代获得原问题的近似解.针对Sioux Falls network展开数值试验并对数值结果进行了对比分析.计算结果表明:在随机交通网络环境下,无约束和有约束条件下求解的最可靠路径是不同的;不同的资源约束条件下求解的最可靠路径也是不同的,资源约束条件对交通网络中最可靠路径的选择有很大的影响.

In order to simulate the behavior of route choice considering risk with resource constraints in traffic network, the mathematical model of constrained reliable shortest path problem in stochastic traffic network is established and its dual problem is discussed. Gradient descent algorithm is used to solve the dual problem, and obtain the upper and lower bounds of the optimal value of the original problem. The approximate solution of the original problem is obtained by iterative approximation. Numerical test is developed on the Sioux Falls network and the numerical results are analyzed. Numerical results show that the reliable shortest paths obtaining under resource unconstraint and constraint are different, and the reliable shortest path obtaining under different resource constraint is also different in stochastic traffic network; the resource constraint has a great influence to the choice of reliable shortest path.