Zijie Zhou
Papers
1
Total Citations
2
H-Index
1
About
Zijie Zhou is an emerging researcher in the field of industrial engineering and intelligent logistics, with a primary focus on supply chain optimization and robotic task allocation. His most-cited work, "Research on Optimization Model of Supply Chain Robot Task Allocation Based on Genetic Algorithm and Software Practice" (2025), introduces a novel framework that integrates genetic algorithms with practical software implementation to enhance the efficiency of automated warehouse systems. This paper, with 2 citations in its early publication stage, demonstrates Zhou’s ability to bridge theoretical optimization models with real-world software deployment—a critical skill in modern supply chain management. His contributions lie in addressing the NP-hard challenge of multi-robot coordination, proposing a scalable solution that reduces task completion time and energy consumption. Zhou’s work is particularly notable for its emphasis on software practice, providing a replicable blueprint for industry adoption. As a researcher early in his career, his citation trajectory suggests growing recognition among peers in robotics and operations research. For students and researchers, Zhou’s approach exemplifies how combining algorithmic innovation with practical validation can drive impactful advances in automated logistics.
Research Focus
Key Achievements
Top Papers
- 1