Design and simulation of intelligent cross-border e-commerce logistics system based on genetic algorithm technology of artificial intelligence

With the rapid development of cross-border e-commerce, the logistics system behind it faces various challenges such as complex routes, diverse transportation modes, and unpredictable customs clearance procedures. To address these challenges, this study proposes a design and simulation of an intelligent cross-border e-commerce logistics system based on genetic algorithm technology of artificial intelligence.The proposed system utilizes genetic algorithm techniques to optimize the logistics route planning, transportation mode selection, and customs clearance process. The genetic algorithm is employed to search for the optimal combination of routes, transportation modes, and customs procedures, considering various factors such as cost, time, and reliability. The system takes into account real-time data, including transportation costs, transit times, customs regulations, and historical shipment information, to make informed decisions and continuously improve the logistics efficiency.The simulation of the proposed system is conducted using historical cross-border e-commerce shipment data. The system is evaluated based on performance metrics such as transportation cost, delivery time, and customer satisfaction. The results demonstrate that the intelligent cross-border e-commerce logistics system based on genetic algorithm technology can effectively optimize the logistics process, reduce costs, and improve customer satisfaction.