Yingying Wu

Papers

Total Citations

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About

Yingying Wu is a leading researcher in the field of logistics and warehouse automation, with a primary focus on the modelling, design, and optimization of automated storage and retrieval systems. Her most cited work, "Modelling and design for a shuttle-based storage and retrieval system" (2020), has garnered 30 citations and stands as a key contribution to the efficient operation of modern part-to-picker order picking systems. In this seminal paper, Wu developed a novel performance estimation algorithm grounded in queuing theory, enabling accurate prediction of system throughput and response times. She further advanced the field by creating a cost-minimization design algorithm that identifies the most economical configuration for shuttle-based systems, directly addressing the industry's need for scalable and cost-effective automation. This work bridges the gap between theoretical queuing models and practical warehouse design, offering engineers a robust tool for optimizing system performance while reducing capital expenditure. Wu’s research is particularly impactful for students and practitioners in industrial engineering, operations research, and supply chain management, as it provides a clear, data-driven framework for tackling real-world logistics challenges. Her contributions continue to influence the evolution of intelligent warehousing solutions.