基于粒子群算法的快速路投资优化方法

从投资影响交通网络容量出发,提出一种新的以元胞传输模型CTM(cell transit model)理论为基础的快速路投资优化方法.首先,对元胞传输模型进行改进以实现局部匝道控制;其次,利用粒子群智能优化方法,构造了元胞通行能力优化问题的粒子群表达方法;并定义了总行车里程(TDT)和系统总延误(TD)作为衡量快速路系统的性能指标.计算结果显示投资前TDT为12 004 874m,TD为3 582 405.1s,投资后TDT为13 128 283m,TD为3 537 468.7s,总行车里程投资后较投资前增加了1 123 409m,总延误投资后较投资前减少了44 936.4s.结果分析表明,新优化方法使总行车里程显著增长,使系统总延误显著降低,提高了整个路网性能.该投资优化方法可以较好地解决快速路投资优化问题.

Decision Method for Express Way Investment Based on a Particle Swarm Algorithm

From the view point of the affection of investment on traffic network capacity,a new kind of expressway investment optimization method based on the cell transmission model (CTM) theory was put forward.The cell transmission model was improved in order to realize the local ramp control.A particle swarm expression method for the meta cell capacity optimization problem was constructed by using the particle swarm intelligent optimization method.And the total mileage (TDT) and system delay (TD) were defined as a measure of the performance of expressway system.The calculation results show that before the investment,the TDT is 12 004 874 m,the TD is 3 582 405.1 s,and after investment,the TDT is 13 128 283 m,increased by 1 123 409 m,the TD is 3 537 468.7 s,reduced by 44 936.4 s.The results show that the new optimization method makes the total mileage significantly grow and the total delay significantly reduce.The performance of the entire road network is also improved.The investment optimization method can better solve the optimization problem of expressway investment.