动态需求背景下的出租车运力规模优化方法

基于出租车需求与运力规模之间的动态制衡关系,建立确定出租车运力规模的双层规划模型. 上层模型以高峰时段乘客等车时间最短和平峰时段出租车空载率最低为目标,建立双目标规划模型;下层模型建立需求与运力规模之间的动态变化关系,求出当前运力下的出租车需求. 采用遗传算法和线性迭代法对模型求解,并以大连市出租车现状为实例进行分析. 研究表明,大连市目前的出租车运力规模偏低,导致高峰期间乘客等车时间偏长,与大连市的情况相符. 另外,在运力规模存在较大不足时,增加运力可以大量吸引出租车需求,当需求与运力规模接近平衡时,需求对运力的增长不再敏感.

Optimization Model of Taxi Fleet Size Under Dynamic Demands

Bi-level programming for designing taxi quantity was established based on the dynamic equilibrium relationship between the fleet size and taxi demand. The upper model employed a double-objective function to minimize the passenger waiting time at peak hours and the taxi unloaded ratio at off-peak hours; the lower model provided a method to decide the demand when the quantity of taxi was known. Finally, the proposed solution was calculated based on multi-object genetic algorithm and linear iteration, and validated using the taxi statistics in Dalian. The results show that, the taxi quantity is not adequate and leads to longer passenger waiting time. It is consistent with the actual conditions in Dalian. The results also show that the expanding of capacity scale can attract a large number of taxi demands when there is a large lack of capacity scale. However, the demand for capacity growth is no longer sensitive when demand and capacity scale are close.