Short response time for order processing is important for modern warehouses, which can be potentially achieved by adopting appropriate processing policy. The parallel processing policy have advantages in improving performance of many autonomous storage and retrieval systems. However, researchers tend to assume a sequential processing policy managing the movement of independent resources in shuttle-based compact storage systems. This paper models and analyses a single-tier of specialized shuttle-based compact storage systems under parallel processing policy. The system is modeled as a semi-open queueing network with class switching and the parallel movement of shuttles and the transfer car is modeled using a fork-join queueing network. The analytical model is validated against simulations and the results show our model can accurately estimate the system performance. Numerical experiments and a real case are carried out to compare the performance of parallel and sequential processing policies. The results suggest a critical transaction arrival rate and depth/width ratio, below which the sequential processing policy outperforms the parallel processing policy. However, the advantage of sequential processing policy is decreasing with the increasing of shuttle number, transaction arrival rate and depth/width ratio. The results also suggest an optimal depth/width ratio with a value of 1.75 for minimizing the expected throughput time in the real system. Given the current system configurations, the parallel processing policy should be considered when the number of shuttles is larger than 2 or the transaction arrival rate is larger than 24 per hour.
Research on Autonomous Vehicle Storage and Retrieval System Cargo Location Optimization in E-commerce Automated Warehouse
