Designing efficient warehouse management systems is essential to improve business performance. The use of autonomous guided vehicles (AGVs) in logistic processes and material handling systems (MHS) improves productivity and reduces costs. However, determining the appropriateness and financial feasibility of acquiring a fleet of AGVs, together with the definition of their path layout, routing schemes, operation tasks, and network flow, becomes a complex problem when designing flexible manufacturing systems (FMS). This study aids the design of a fleet of AGVs by means of a fuzzy-set qualitative comparative analysis (fsQCA), which makes it possible to measure the level of satisfaction of managerial decision makers. It enables us to identify a combination of factors that lead to stakeholders' satisfaction while dealing with uncertain environments due to the heterogeneous nature of decision makers and factors. Our methodology has been applied to multi-criteria decision-making analysis, resulting in greater transparency, fairness, social equity, and consensus among stakeholders.