Simulation based regression analysis for rack configuration of autonomous vehicle storage and retrieval system

In this study, a simulation based regression analysis for rack configuration of an autonomous vehicle storage and retrieval system (AVS/RS) is presented. We develop a mathematical function for rack configuration of an AVS/RS that reflects the relationship between the output (response) and the input variables (factors) of the system. In the regression model, the output is the average cycle time for storage and retrieval and the input variables are the number of tiers, aisles and bays that determine the size of the warehouse. The simulation model of the system is developed using ARENA 12.0, a commercial software. We use MINITAB statistical software to complete the statistical analysis and to fit a regression function. Two different approaches are used for developing the regression analysis - stepwise regression and the best subsets. We optimize the regression function using the LINGO software. We apply this approach to a company that uses AVS/RS in France.