Abstract Automation is rapidly transforming warehouse operations by improving productivity, safety, and long-term cost performance. However, transitioning from manpower-based systems to automated solutions remains a complex decision-making challenge due to uncertainty and competing performance criteria. To address this challenge, this study applies an integrated fuzzy multi-criteria decision-making (MCDM) framework to compare automated and manpower-based warehousing systems. Four established fuzzy MCDM methods, Fuzzy EDAS, Fuzzy TOPSIS, Fuzzy AHP, and Fuzzy VIKOR, are integrated within a single evaluation framework to provide a more comprehensive perspective than any individual method alone. A further methodological contribution is a targeted sensitivity analysis applied to Fuzzy EDAS and Fuzzy VIKOR, the two methods most responsive to criterion-weight variation. This analysis tests ranking robustness under alternative weighting scenarios and strengthens result credibility. Six core evaluation criteria, productivity, safety, flexibility, initial investment, annual expense, and error rate, are employed, reflecting both operational performance and financial considerations. The results consistently indicate that automated warehousing systems outperform manpower-based alternatives in terms of productivity, safety, and long-term operating expenses, while manual systems retain advantages in flexibility and lower initial investment. Overall, this study contributes to the fuzzy MCDM literature by demonstrating how multi-method integration and structured sensitivity analysis enhance the robustness of decision outcomes, while also offering practical insights for managers evaluating warehouse automation strategies.
SOYGUDER et al. (Mon,) studied this question.