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About

Longhai Li is a leading researcher in swarm intelligence and mobile robot navigation, specializing in the development of enhanced metaheuristic algorithms for path planning and obstacle avoidance. His major contributions lie in systematically improving the performance of nature-inspired optimization algorithms—such as the Dung Beetle Optimization (DBO), Grey Wolf Optimization (GWO), and Sparrow Search Algorithm (SSA)—by addressing their core limitations in balancing global exploration and local exploitation. Li’s work has produced high-impact solutions that significantly boost convergence accuracy, iteration speed, and robustness against local optima, directly advancing autonomous navigation systems. His most-cited paper, "Enhancing Swarm Intelligence for Obstacle Avoidance with Multi-Strategy and Improved Dung Beetle Optimization Algorithm in Mobile Robot Navigation" (2023), has garnered 23 citations, while his "Enhanced Grey Wolf Optimization Algorithm for Mobile Robot Path Planning" (2023) has received 20 citations, reflecting the practical relevance of his innovations. With a focus on multi-strategy collaborative optimization, Li’s algorithms are widely applicable in robotics and engineering, making him a key figure in the evolution of intelligent optimization techniques.