基于众包的外卖配送订单选择研究

各外卖平台均提供了兼职配送员参与众包服务的渠道。与专职配送员相比，兼职配送员有着“路径开放、时间有限、最终目的地确定”等诸多不同的特点。基于兼职配送特点，为了提高众包配送员的接单效率，提高兼职收益，对众包模式下的订单选择及订单执行路径进行深入分析，提出将二者进行统一考虑的双层算法：在底层建立众包外卖配送路径规划模型，并使用改进的遗传算法求解；第2层利用贪心算法调用底层模型，通过比较配送收益进行订单选择，使得兼职人员的配送收益最大。通过算例实验，验证模型及算法的合理性及有效性条件，发现算法的计算时间随备选订单数量增加线性增加。在现实应用中，需要通过对备选订单进行打分排序，控制“订单池”规模，则能在可接受时间内得到较高质量的选择结果。

A Research on Take-away Delivery Task Selection in Crowdsourcing

Nearly all the take-away platforms provide opportunities of part-time delivery service. Compared with full-time staff, part-time deliverers have several features when they participate in crowdsourcing delivery, including "multiple delivery path, limited working time, fixed destination and etc". Considering these characters, a research is made on take-away distribution task selection and task routing problem in crowdsourcing mode and a two-layer algorithm is proposed in order to enhance deliverers' efficiency and raise their revenue. A delivery routing problem model is built in the bottom layer, and solved with improved genetic algorithm. The upper layer adopts greedy algorithm and compares delivery revenue according to the model in the bottom layer to select tasks, so that the crowdsourcing workers' revenue can reach the largest level. A numerical case is given to test and verify the effectiveness of model and algorithm, the solving time increases linearly with the number of potential orders. In practice, this method can achieve a relatively high-quality solution in an acceptable time when the scale of alternate orders has been controlled.