The four-way-shuttle-based storage and retrieval system is a recent innovative intelligent vertical warehousing system that has been widely applied in manufacturing and e-commerce environments due to its high flexibility and density. As a complex multi-device cooperative operational system, this system features the parallel operation of multiple elevators and four-way shuttles. During large-scale-batch inbound operations, the quality of scheduling solutions for inbound-operation equipment significantly impacts the system’s efficiency and performance. In this paper, a detailed analysis of the inbound-operation process in the system is conducted, taking into consideration the motion characteristics of both the elevators and four-way shuttles. Furthermore, we establish operational time constraints that account for equipment acceleration and deceleration characteristics and introduce a flexible flow-shop-scheduling model to address the scheduling problem in the system. Additionally, we propose an improved genetic algorithm based on double-layer encoding to solve this problem. Comparative experiments with a traditional genetic algorithm and ant-colony algorithm demonstrate the superior efficiency and accuracy of our approach. Finally, the effectiveness of the proposed algorithm is validated through comparisons with large-scale practical experiments.

As the four-way shuttle vehicle is prone to overturning in finished grain storage during acceleration and deceleration, an overturning mechanical model is constructed. The design factors analyzed include grain bag height, vehicle and grain bag mass, and the type of grain’s effect on the vehicle’s anti-overturning stability. The critical overturning condition of the shuttle vehicle during operation is also determined as a result of this analysis. With the critical overturning condition, the speed control of the shuttle vehicle based on the fuzzy PID method is carried out to improve the anti-overturning stability. Significant details are made about the fuzzification of input and output variables, determination of membership function, establishment of the fuzzy rule base, fuzzy reasoning, and defuzzification. Finally, the comparative simulation model of fuzzy PID and conventional PID in the MATLAB/Simulink platform showed that the fuzzy PID control method had the advantages of fast convergence and quick response to the speed control of the four-way shuttle vehicle.