Multi-speed configuration of AS/RS amidst responsiveness and energy efficiency trade-off: metamodel-based simulation–optimization

Automated Storage and Retrieval System (AS/RS) is driven by multiple motors for loading and unloading the items (z-axis) onto the fork or stacker, then moving the items horizontally (x-axis) and vertically (y-axis) at a time. Thus, it is practical to determine the speed configuration for each movement. To be responsive, it is reasonable to set the speed as fast as possible. However, high speed leads to high energy consumption which is undesirable in the context of green warehousing. Given that the speed changes dynamically, it is important to have an advanced optimization model for balancing both objectives and providing accurate estimation. This study proposed metamodel-based simulation–optimization (MSO) allowing to jointly optimize four speed-related variables namely horizontal speed (x), vertical speed (y), fork or depth speed (z), and acceleration/deceleration under the dynamicity of AS/RS. A case study was given in a warehouse comprising five cranes and ten racks. Using Desirability Function Analysis, the optimal speed configuration is obtained efficiently for minimizing travel time and energy consumption of AS/RS. The result also shows that row-based storage provides better responsiveness and energy efficiency than random-based storage. Further, rack design also indicates a significant impact on the AS/RS speed configuration.