Research on Logistics Distribution Routing Problem of Unmanned Vehicles Based on Genetic Simulated Annealing Algorithm

Nowadays, unmanned logistics distribution has become a necessity for development. This paper proposes a vehicle routing model for logistics scheduling and distribution intending to minimize the distribution cost by integrating intelligent scheduling and path planning systems. The genetic simulated annealing algorithm is designed combining with the genetic algorithm and the simulated annealing algorithm. In this scheme, electric unmanned vehicles are used for urban logistics distribution to improve efficiency and reduce costs. At the same time, factors such as vehicle load, customer time window, and vehicle mileage limit are taken into consideration. Finally, the effectiveness and superiority of the proposed algorithm are verified by applying it to solve a specific case.