Vehicle path optimization with time window and simultaneous delivery and pickup under fuzzy demand

In order to improve the vehicle loading rate in the logistics and distribution process, this paper studies the vehicle routing problem with time window and simultaneous delivery and pickup under fuzzy demand. Triangle fuzzy numbers are introduced to describe the uncertainty of customer demand and construct a multi-objective function model with the goal of minimum total cost. Genetic algorithm (GA) is used to solve this problem. Compared with the simple delivery scheme and simple pickup scheme, the results show that the designed model and algorithm optimize the vehicle path and significantly reduce the number of vehicles, improve the average vehicle load rate and reduce the enterprise cost.