Tingting Dong
Papers
6
Total Citations
61
H-Index
4
About
Tingting Dong is a researcher specializing in multi-robot systems, intelligent warehouse automation, and evolutionary optimization algorithms. Her work sits at the intersection of swarm intelligence and real-world logistics challenges, with a particular focus on developing sophisticated computational methods for task allocation in complex robotic environments. Dong's most significant contribution is her 2020 paper introducing a hybrid many-objective competitive swarm optimization algorithm for large-scale multi-robot task allocation, which has garnered 35 citations and represents a meaningful advance in handling the combinatorial complexity of coordinating numerous robots simultaneously. Her earlier foundational work applied improved ant colony algorithms to logistics robot task allocation, demonstrating a consistent commitment to bio-inspired optimization techniques across multiple studies from 2016 to 2018. She has also contributed to e-commerce warehouse efficiency through clustering algorithms for order batching, addressing the practical operational demands of modern fulfillment systems. Her most recent work (2025) on adaptive hybrid response mechanisms for dynamic multi-objective optimization signals an evolving research agenda tackling time-varying, real-world robotics problems. With publications spanning nearly a decade and cumulative citations exceeding 60, Dong's research offers valuable tools for engineers and scientists working to make autonomous warehouse robotics more scalable and efficient.
Research Focus
Key Achievements
Top Papers
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