Mahmut Tutam
Papers
3
Total Citations
28
H-Index
2
About
Mahmut Tutam is a rising scholar at the intersection of operations research, logistics, and robotics, with a focused expertise in designing intelligent warehouse systems. His research centers on optimizing order-picking processes—the most labor-intensive and costly activity in warehousing—by integrating collaborative robots (cobots) and advanced storage architectures. Tutam’s major contributions include pioneering frameworks that move beyond traditional cost-minimization models to incorporate real-world complexities like demand skewness and human-robot collaboration. His most cited work, “To walk or not to walk? Designing intelligent order picking warehouses with collaborative robots” (2024, 15 citations), provides a decision-support tool for managers weighing robotic investment against manual labor, while “Consideration of skewness in designing robotic compact storage and retrieval systems” (2024, 11 citations) introduces statistical distribution modeling to improve system throughput and space utilization. Together, these papers have garnered early impact, signaling their relevance to both academia and industry amid the e-commerce boom. Tutam also contributes to Turkish-language literature, addressing local logistics challenges. His work is particularly notable for bridging theoretical optimization with practical, data-driven design, offering actionable insights for next-generation fulfillment centers.
Research Focus
Key Achievements
Top Papers
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