Multi-vehicle dynamic vehicle routing optimization in green logistics distribution

Aiming at the problem of multi-vehicle dynamic routing optimization under low carbon conditions, the research process was divided into two stages: Pre-optimization and dynamic adjustment. The optimization model was constructed with the lowest total cost as the objective function, and the improved adaptive genetic algorithm (IAGA) was used to solve the model. In the pre-optimization stage, IAGA algorithm is used to generate the initial distribution scheme under the constraints of meeting the store demand, returns, vehicle fuel volume, working hours and road conditions. In the dynamic adjustment stage, the changes in store demand, road conditions, temporary returns, as well as the current distribution vehicle location, cargo load and fuel volume are integrated. Through the experimental analysis, the feasibility of the model and algorithm is verified, and the total cost is effectively reduced, which provides a good reference for the formulation of enterprise distribution strategy. © 2024 Systems Engineering Society of China. All rights reserved.