  Since the rising of the takeaway ordering platform, the M platform has taken
the lead in the industry with its high-quality service. The increasing order
volume leads the competition between platforms to reduce the distribution cost,
which increases rapidly because of the unreasonable distribution route. By
analyzing platform distribution's current situation, we study the vehicle
routing problem of urban distribution on the M platform and minimize the
distribution cost. Considering the constraints of the customer's expected
delivery time and vehicle condition, we combine the different arrival times of
the vehicle routing problem model using three soft time windows and solve the
problem using a genetic algorithm (GA). The results show that our model and
algorithm can design the vehicle path superior to the original model in terms
of distribution cost and delivery time, thus providing decision support for the
M platform to save distribution cost in urban distribution in the future.
