Abstract

With the development of tourism, vehicle traffic scheduling in scenic spots has gradually become a research hotspot. Aiming at the problem of vehicle scheduling and route planning at multiple service points in the scenic spot, we propose a method to minimize the total cost of vehicle scheduling and route planning tasks at the service point under the constraints of the weight of the required goods and the vehicle volume. First, we classify the demand points and assign the corresponding service points; then we aim to minimize the cost of vehicle scheduling and establish a nonlinear programming model under the constraints of the weight of the demand product and the volume of the vehicle; then, we will The model is reduced to a single service point TSP problem, and based on the improved ant colony algorithm, a solution model based on TSP is designed. The experimental results show that our model and algorithm can make the distribution cost of multiple service points the lowest and the iteration speed is faster.

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