Performance analysis and design trade-offs in warehouses with autonomous vehicle technology

Distribution centers have recently adopted Autonomous Vehicle-based Storage and Retrieval Systems (AVS/RSs) as a potential alternative to traditional automated storage and retrieval systems for processing unit-load operations. The autonomy of the vehicles in an AVS/RS provides a level of hardware sophistication, which can lead to the improvements in operation efficiency and flexibility that will be necessary in distribution centers of the future. However, in order to exploit the potential benefits of the technology, an AVS/RS must be designed using a detailed understanding of the underlying dynamics and performance trade-offs. Design decisions such as the configuration of aisles and columns, allocation of resources to zones, and vehicle assignment rules can have a significant impact on the performance of AVS/RSs. In this research, the performance impact of these design decisions is investigated using an analytical model. The system is modeled as a multi-class semi-open queuing network with class switching and a decomposition-based approach is developed to evaluate the system performance and obtain insights. Numerical studies provide various insights that could be useful in the design conceptualization of AVS/RSs.