Hongyan Sang
Papers
7
Total Citations
118
H-Index
5
About
Hongyan Sang is a leading researcher in intelligent robotics and multi-objective optimization, with a particular focus on agricultural and service robotics. Their work centers on developing advanced metaheuristic algorithms to solve complex task allocation, scheduling, and path planning problems in distributed and cooperative robotic systems. Sang’s most impactful contribution is an improved iterated greedy algorithm for distributed robotic flowshop scheduling with order constraints (2021, 39 citations), which addresses critical challenges in manufacturing logistics. They have also pioneered multi-objective teaching-learning-based and evolutionary algorithms for cooperative task allocation between weeding robots and spraying drones (2024, 27 and 25 citations respectively), directly advancing precision agriculture. More recently, Sang has developed self-learning optimization mechanisms for multi-objective path planning (2025, 14 citations) and integrated task-path planning approaches for agricultural robots (2025). Their earlier foundational work on firefly and Pareto-based algorithms for multi-objective path planning (2018) established the basis for autonomous navigation in service robots. With a growing citation record and a clear trajectory toward practical, real-world robotic coordination systems, Sang’s research is shaping the future of intelligent, autonomous agricultural and service robotics.
Research Focus
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Top Papers
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