Multi Modal Transportation Path Selection of Coal based on Genetic Algorithm

Abstract

In order to solve the problem of selecting transportation routes and transfer nodes reasonably in the process of multimodal logistics distribution, the author proposes a coal transportation multimodal transportation path selection based on genetic algorithm. Firstly, this paper establishes an object function for routing according to the features of multi-modal transport, which has the minimum transport time, the minimum transport length and the minimum transport cost. Secondly, we design appropriate GA components, and get a multiobjective route optimal model for multimodal transport by using GA. Taking into account the high transportation costs of coal as a bulk commodity, a coal transportation multimodal transport path optimization model was constructed with the total transportation cost as the objective function of the model, and the minimum economic cost as the objective. At last, this paper applies GA and MATLAB to resolve the case. Experiments showed that the starting population was 90, with a cross rate of 0.6 and a mutation rate of 0.02. After 100 iterations, it was found that the fitness change between adjacent generations was less than 0.01, indicating that the population mean of the running results had stabilized. At this point, it can be considered that the results have converged. This method validates the practicality of the established model and provides a reference for logistics enterprises to carry out multimodal transportation.