Abstract
In the actual vehicle logistics distribution process, the number of vehicles and the choice of distribution path determine the logistics cost. Aiming at the problem of high logistics cost, this paper establishes a multi-objective vehicle logistics path optimization mathematical model considering the distribution process and the number of vehicles. In order to solve the model, a hybrid ant colony particle swarm optimization algorithm is proposed. The algorithm integrates the particle swarm algorithm into the ant colony algorithm, which makes the ant colony algorithm have the characteristics of “particles”, speeds up the search speed of the ant colony algorithm, and reduces the defect of falling into local convergence. The simulation results show that the path optimization model and its hybrid algorithm have fast convergence, can effectively reduce the distribution process and the number of vehicles, and can reduce a large number of vehicle logistics costs, which provides a valuable reference for the whole vehicle logistics path planning.
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