Modeling and Scheduling of tier-to-tier shuttle-based storage and retrieval systems

This paper presents a model for describing the storage/retrieval time of a tier-to-tier shuttle-based storage and retrieval systems (SBS/RS). By using the Genetic-based particle swarm optimization (GPSO), the storage/retrieval scheduling optimization problem of the system is effectively solved. We analyzed the actual running process of the lift and shuttle carriers in the system, considered the acceleration and deceleration characteristics of the lift and shuttle carriers during the movement, and established the travel time model of the lift operation. Based on the characteristics of the model, we designed the GPSO to optimize the model. By introducing crossover operation and mutation operation in the algorithm, the algorithm avoids prematurely falling into the local optimal solution and improves the performance of the algorithm. The example analysis shows that compared with GA and PSO, GPSO runs faster and optimizes efficiency, which can effectively shorten the operation time of SBS/RS and improve system efficiency.