Guo Wei

University of North Carolina at Pembroke

Papers

Total Citations

H-Index

About

Guo Wei is a rising force in computational intelligence, specializing in metaheuristic optimization and autonomous path planning. His research focuses on developing nature-inspired algorithms that solve complex engineering problems with unprecedented efficiency. Wei's landmark work, "HG-SMA: hierarchical guided slime mould algorithm for smooth path planning" (2023, 47 citations), introduced a novel hierarchical framework that dramatically improves the smoothness and feasibility of robot trajectories, bridging the gap between theoretical swarm intelligence and real-world navigation. Building on this, his "ACEPSO: A multiple adaptive co-evolved particle swarm optimization" (2024, 40 citations) presents a breakthrough in adaptive co-evolution, enabling particle swarms to dynamically reconfigure their search strategies for challenging engineering design tasks. These contributions have earned him growing recognition for transforming abstract optimization concepts into practical tools for robotics and industrial systems. With both papers already accumulating significant citations within their first year, Wei's work is rapidly shaping how researchers approach multi-objective optimization and path planning—making him a key figure to watch in the evolution of intelligent algorithms.