In recent years, the adoption of Industry 4.0 principles within intralogistics has grown significantly due to the increasing need of companies for flexible and smart factories. This shift is particularly evident in material handling, where automation has become the most common trend. Specifically, Automated Guided Vehicles (AGVs) and Autonomous Mobile Robots (AMRs) represent the most important examples of automated technologies and have been widely analysed. However, there is a gap in the current literature on how the topological complexity of a factory layout influences the performances of an AGV and AMR system. Given this context, the thesis aims to bridge the gap by proposing a simulation based method to support companies in the selection of the most ideal automated material handling systems, between AGV and AMR, by taking in considerations the impact of the layout complexity on their performance.