论文部分内容阅读
提出了一种优化的迭代降维算法求解混合交通网络设计问题. 混合(连续/离散) 交通网络设计问题常表示为一个带均衡约束的数学规划问题,上层通过新建路段和改善已有路段来优化网络性能,下层是一个传统的 Wardrop 用户均衡模型. 迭代降维算法的基本思想是降维,先保持一组变量(离散/连续) 不变,交替地对另一组变量(连续/离散) 实现最优化. 以迭代的形式反复求解连续网络设计和离散网络设计问题,直至最后收敛到最优解. 通过一个数值算例对算法的效果进行了验证.
An optimized iterative dimensionality reduction algorithm is proposed to solve the hybrid traffic network design problem.The mixed (continuous / discrete) traffic network design problem is often expressed as a mathematical programming problem with equilibrium constraints, and the upper layer is optimized by the new road segment and the improvement of existing road segments Network performance, the lower layer is a traditional Wardrop user equilibrium model.The basic idea of iterative dimensionality reduction algorithm is to reduce dimension, to keep a group of variables (discrete / continuous) unchanged and to alternately implement another group of variables (continuous / discrete) Optimization.We iteratively solve continuous network design and discrete network design iteratively until finally converge to the optimal solution.A numerical example is used to verify the effectiveness of the algorithm.