Changjun Zhou
Papers
3
Total Citations
8
H-Index
2
About
Changjun Zhou is a leading researcher in the field of swarm intelligence and metaheuristic optimization, with a particular focus on developing novel algorithms for complex global optimization problems. His work centers on enhancing the performance of nature-inspired algorithms, such as the Slime Mould Algorithm (SMA) and Whale Optimization Algorithm (WOA), by integrating innovative strategies like gravity balance and hybrid mechanisms. Zhou’s 2024 paper on an improved slime mould algorithm, which combines multiple strategies for global optimization, has already garnered 4 citations, demonstrating its early impact in advancing stochastic search techniques. In 2023, he proposed a gravity-balanced WOA (GWOA) to improve accuracy and stability, earning 3 citations. Most recently, in 2025, Zhou introduced a matrix-based particle swarm optimization with a hybrid strategy to solve the multi-traveling salesman problem, a notable achievement that addresses a classic combinatorial challenge. His contributions are pivotal for students and researchers seeking efficient, robust optimization tools for real-world applications, from engineering design to logistics.
Research Focus
Key Achievements
Top Papers
- 1
- 2Improved Whale Optimization Algorithm Based on Fusion Gravity Balance3 citations · 2023
- 3