Zhaoquan Huang

Papers

Total Citations

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About

Dr. Zhaoquan Huang is a prominent researcher in computational intelligence and combinatorial optimization, with a particular focus on solving complex real-world routing and scheduling problems. His most cited work, "Matrix-based particle swarm optimization with hybrid strategy for multi-traveling salesman problem," exemplifies his innovative approach to enhancing swarm intelligence algorithms. In this study, Dr. Huang introduced a novel matrix representation combined with a hybrid strategy to address the multi-traveling salesman problem (mTSP), a notoriously difficult NP-hard challenge with applications in logistics, transportation, and network design. His contribution lies in effectively balancing exploration and exploitation in particle swarm optimization, leading to improved solution quality and convergence speed. While his citation count is still growing, this work has already attracted attention for its practical utility and methodological rigor. Dr. Huang’s research bridges the gap between theoretical algorithm design and applied optimization, offering scalable tools for industries requiring efficient route planning. His ongoing work continues to push the boundaries of metaheuristic algorithms, making him a rising figure in operations research and artificial intelligence.