Haozheng Meng
Papers
1
Total Citations
3
H-Index
1
About
Haozheng Meng is a rising researcher in computational intelligence and financial optimization, whose work bridges evolutionary algorithms and complex decision-making under uncertainty. His most-cited paper, "A differential evolution algorithm with diversity dynamic adjustment and two-phase constraint handling strategy for solving a pension fund investment problem under market uncertainty" (2025, 3 citations), introduces a novel hybrid approach that dynamically adjusts population diversity and employs a two-phase constraint handling mechanism to navigate the high-dimensional, risk-laden landscape of pension fund allocation. This contribution addresses a critical gap in applying metaheuristics to real-world financial systems, where traditional methods often fail under volatile market conditions. Meng’s algorithm demonstrates how adaptive diversity control can prevent premature convergence while maintaining solution feasibility, offering a robust tool for long-term investment strategy. Though early in his career, his work signals a promising trajectory in integrating evolutionary computation with practical financial engineering, making him a researcher to watch for innovations in uncertainty-aware optimization.
Research Focus
Key Achievements
Top Papers
- 1