随机需求多阶段离散交通网络设计

Multi-stage Discrete Network Design Under Stochastic Demand

为了降低交通规划方案的风险,提高规划方案建设时序选择的整体效益,以随机OD需求分布为前提,以随机双层规划理论为基础,建立多阶段网络设计模型,同步优化网络规划最终形态和建设时序.给出了基于MonteCarlo模拟和遗传算法的模型求解算法.Nguyen Dupuis网络的测试分析表明,资金投入的时段分布对网络规划建设决策有重要影响,前期增加预算可以提高规划方案的全局效益;同时需求不确定性以及决策者风险偏好对最终规划结果也有重要影响.

To reduce the risk of transportation planning scheme and improve the whole benefit of project selection in different stages, a multi-stage discrete network design model under stochastic OD demand is set up to determine the optimal project scheduling with stochastic bi-level optimization. The proposed model, a combinatorial optimization problem, is solved using Monte Carlo simulation and genetic algorithm. Numerical results on Nguyen Dupuis network indicate that the distribution of funds has a great impact on decision making and the system performance can be improved with more funds in early days of the whole planning period. Besides, demand uncertainty and planner＇s preferences are also crucial to the final program.