Jinglin Wang

Macau University of Science and Technology

Papers

Total Citations

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About

Jinglin Wang is a leading researcher in transportation optimization and intelligent logistics, with a focus on developing advanced algorithms for dynamic shortest path problems. Their most-cited work, "An Improved Discrete Jaya Algorithm for Shortest Path Problems in Transportation-Related Processes" (2023, 12 citations), introduces a novel metaheuristic that adapts the Jaya algorithm to discrete environments, addressing the frequent path recalculation challenges posed by real-time data from Internet of Things sensors. This contribution has direct applications in intelligent transportation systems, robot path planning, and smart logistics, where environmental changes demand rapid, efficient routing solutions. Wang’s research bridges the gap between theoretical optimization and practical engineering, enabling more responsive and robust decision-making in complex, dynamic networks. Their work is recognized for its practical impact, offering a computationally efficient alternative to traditional methods, and has been cited by peers exploring adaptive algorithms in transportation and robotics. Wang’s ongoing contributions continue to shape the field of smart mobility, making them a key figure in the evolution of data-driven transportation systems.