随着城市居民绿色低碳出行思想的提高, 网约车合乘出行方式应运而生. 但由于合乘模式涉及到的行驶路线问题, 乘客与乘客、乘客与驾驶员之间容易产生分歧, 并且网约车合乘出行模式的相关成本不明确等诸多问题, 网约车合乘模式没有被大范围推广和应用. 针对网约车合乘出行模式存在的问题, 研究并构建了网约车合乘路径优化模型, 模型中考虑了车辆等待时间成本、行驶距离成本、收益、容量约束以及时间窗约束等. 针对网约车合乘模型的特点, 并基于遗传算法思想, 研究设计了满足合乘模型约束条件的求解遗传算法. 并使用Matlab软件运行算法程序对算例进行求解, 运行44.08 s得到最大利润
With the improvement of urban residents’ consciousness of green and low-carbon travel, ride-sharing travel of online car-hailing emerged at the historic moment. However, due to the driving route issue involved in the ride-sharing mode, differences between the passengers and between the passengers and the driver are highly likely to occur. Moreover, the costs of this ride-sharing travel mode remain to be clarified. For the above-mentioned and various other reasons, the ride-sharing mode has not been widely promoted and applied. To address the problems with this travel mode, this study constructs a route optimization model for online car-hailing ride-sharing. and the model takes into account the cost of waiting time, that of driving distance, benefit, capacity constraint, time window constraint, etc. According to the characteristics of the ride-sharing model, a solving genetic algorithm satisfying the constraints on the ride-sharing model is designed by drawing on the genetic algorithm. Matlab software is used to run the algorithm program and thereby solve the calculation example, and a maximum profit of 6 906.297 1 CNY and the detailed driving route for the vehicle are obtained after the program is run 44.08 s. The experiment shows that an approximate optimal solution for the ride-sharing route can be obtained by the ride-sharing model of online car-hailing constructed and the genetic algorithm designed, which proves the feasibility and effectiveness of the proposed model and algorithm.