Lianshuan Shi

Tianjin University of Technology and Education

Papers

Total Citations

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About

Lianshuan Shi is a researcher specializing in intelligent optimization algorithms and autonomous robotics, with a particular focus on mobile robot path planning. Their work centers on addressing fundamental limitations in classical evolutionary computation methods, most notably the tendency of simple genetic algorithms to converge prematurely toward local optima and produce insufficiently smooth, unstable solutions in complex navigation environments. Shi's most notable contributions include the development of improved genetic algorithm (IGA) frameworks that incorporate novel techniques such as intermediate value insertion and adaptive population initialization through discontinuous continuity methods. These enhancements yield more robust, efficient, and practically deployable path planning solutions for mobile robots — a critical challenge at the intersection of artificial intelligence and autonomous systems. With recent publications in 2022 and 2023 already accumulating citations, Shi's research is gaining traction within the robotics and computational intelligence communities. Their work speaks directly to real-world engineering demands, offering algorithmic refinements that balance exploration and exploitation in optimization search spaces. For students and researchers working on autonomous navigation, swarm intelligence, or evolutionary computation, Shi's contributions represent a meaningful step forward in making genetic algorithms more reliable and effective tools for dynamic, real-world robotic applications.