摘要
研究随机事件条件下单条公交线路不同运营时段内的发车间隔确定方法.对该公交系统中的相关随机事件做了基本假设,依此建立了以社会福利最大为目标函数的多时段发车间隔优化随机期望值模型.由于该模型的目标函数为不连续函数,其不连续点发生在运营时段改变之时,因此设计了混合智能求解算法,其中嵌入了随机模拟、神经网络和遗传算法.并采用一个算例讨论了该发车间隔确定模型的有效性及求解算法的效率.该混合智能算法在求解随机期望值模型时效率较高,但容易陷入局部最优解.
To investigate the headways determining methods for single bus line during different operating time periods under stochastic event conditions, assumptions on stochastic events are made and according to which an expected value model for multiple bus headways optimization aiming at maximal social welfare is formulated. The objective function of the proposed model is discontinuous, its point discontinuities happen at the moment when operation time period changes. A hybrid intelligent algorithm is employed to solve the model, in which stochastic simulation, neutral network, genetic algorithm are embedded. A numerical example is tested to discuss the feasibility of the headways determination model as well as the efficiency of its solution algorithm. This hybrid intelligent algorithm runs at high efficiency when solving the stochastic expected value model, while it is easy to fall into the trap of local optimization.
出处
《北京理工大学学报》
EI
CAS
CSCD
北大核心
2009年第8期676-680,共5页
Transactions of Beijing Institute of Technology
基金
国家"八六三"计划项目(2006AA11Z203)
霍英东基金项目(104007)
北京交通大学重点基金资助项目(2006XZ004)
关键词
多时段发车间隔
随机期望值模型
混合智能算法
随机模拟
神经网络
遗传算法
multiple headways
stochastic expected value model
hybrid intelligent algorithm
stochastic simulation
neural network
genetic algorithm
