摘要
提出了在拥挤网络下利用密度作为观测变量对Origin-Destination(OD)需求进行重构的双层规划模型。上层目标为极小化各个估计值与观测值之间的误差,下层为用户均衡模型。采用KKT条件法将该双层规划转化为相对容易求解的均衡约束规划模型,再用Scholtes松弛化方法求解转化后模型。数值实验结果表明,在拥挤网络下的OD重构问题中,利用密度作为观测变量优于流量作为观测变量,同时在求解方法上,利用KKT条件转换为单层模型的求解方法优于上下层交替求解法。
A bi-level programming model to reconstruct origin-destination(OD)demand by using density as the observed variable under congested network is proposed.The upper-levels minimize the errors on the estimated values and observed values,and the lower-levels are user equilibrium model.For a bi-level programming model,KKT condition method is adopted,it is transformed into a mathematical program with equilibrium constraints which is easier to solve,and then Scholtes relaxation method is used to solve the transformed model.The numerical results show that,using density as the observed variable is better than using flow in the OD reconstruction problem under congested network.Meanwhile,for solving method of bi-level programming model,the method of transforming KKT condition into single-level is superior to the upper-lower alternate algorithm.
作者
李高西
任艺
LI Gaoxi;REN Yi(School of Mathematics and Statistics,Chongqing Technology and Business University,Chongqing 400067;Chongqing Key Laboratory of Social Economy and Applied Statistics,Chongqing 400067)
出处
《工程数学学报》
CSCD
北大核心
2024年第2期279-293,共15页
Chinese Journal of Engineering Mathematics
基金
国家自然科学基金(11901068)
国家应用数学中心项目(ncamc2021-msxm01)
重庆市自然科学基金面上项目(CSTB2022NSCQ-MSX0606)
重庆市研究生导师团队建设项目(yds223010).
