基于用户预约数据的公共自行车高峰期调度研究

Scheduling of Public Bicycle during Peak Period Based on the Customer Reservation Data

围绕公共自行车系统缺乏高峰期需求预测以及系统调度理念,引起调度滞后、用户满意度低等问题展开分析,探讨公共自行车高峰期调度需求预测和系统平均满意度量化的方法,研究公共自行车调度最优化路径问题。在基于用户预约数据的高峰期调度需求预测模型研究基础上,考虑用户满意度,建立最小化调度综合成本的优化调度模型,并采用改进的遗传算法对模型进行求解。以广州市某区域的公共自行车系统为研究对象,对模型进行实例验证。研究结果表明:与常规调度方案相比,综合成本降低了16.6%,系统平均用户满意度提升了28.7%。

The issues of scheduling delay and low customer satisfaction caused by the lack of demand forecast during peak period and the concept of systematic scheduling in the public bicycle system were analyzed. The quantization method of scheduling demand forecast and system average satisfaction of the public bicycle during peak period was discussed; the optimal routing of the public bicycle scheduling was also analyzed. According to the analysis on the scheduling demand forecast model based on the customer reservation data during peak period,the optimal scheduling model to minimize the comprehensive scheduling costs with considering the customer satisfaction level was established,and then an improved Genetic Algorithm was adopted to solve the proposed model.Finally,a case study of the public bicycle system at certain area in Guangzhou was cited to verify the proposed model.Research results show that,compared with the conventional scheduling plan,the comprehensive cost of the proposed model is reduced by 16. 6% and the system average customer satisfaction is improved by 28.7%.