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Commercial Vehicle Transportation Strategy Based on Adaptive Ant Colony Algorithm and CW Algorithm

Reasonable planning of the commercial vehicle supply chain is conducive to improving work efficiency and reducing transportation costs. In this paper, TSP model and VRP model are established corresponding to the question of whether it is necessary to consider the carrying capacity of commercial vehicles. Through the improvement of state transition and pheromone update, Adaptive Ant Colony Algorithm is proposed to solve the TSP model. And this paper uses CW Algorithm based on saving degree to solve the VRP model. The simulation results indicate that the algorithm can effectively improve freight efficiency and reduce transportation costs, which is of great significance for transportation companies to establish an effective commercial vehicle supply chain system.