摘要
基于蒙特卡洛模拟方法建立了环境容量限制下的居民出行总量动力学模型,使用模糊推理方法预测出租车对出行总量的分担率,在此基础上求得了该城市的出租车最佳数量.根据基于激励约束机制的出租车定价模型,结合司机和乘客的共同利益,给出了油价上涨后的调价方案:①将起步价由目前的8元上调到8.5元;②将起租基价公里数由现在的3公里降低到2.75公里;③将每公里单价由1.8元上升到2元.最后,对各模型的进一步改善进行了讨论.
This paper made a dynamic model of total inhabitant OD trips on the limit of the urban traffic capacity based on the method of Monte Carlo simulation, and the taxi sharing ratio of the public traffic was predicted based on the fuzzy reasoning. Finally, the optimal taxi quantity of this city was acquired. Based on constraint and incentive mechanism, an adjusting scheme of taxi price on the benefit of both drivers and customers was given as follows： ① to adjust the start- price from 8RMB to 8.5RMB;②to adjust the start - kilometer from 3km to 2.75km; ③ to adjust the unit price from 1.8RMB per kilometer to 2 RMB. Finally, the improvement of each model was discussed.
出处
《数学的实践与认识》
CSCD
北大核心
2006年第7期121-131,共11页
Mathematics in Practice and Theory
关键词
蒙特卡洛模拟
模糊推理
激励约束机制
monte carlo simulation
fuzzy reasoning
incentive and constraint mechanism
