Improved Nutcracker Optimization Algorithm for UAV Path Planning
Author Information
Author(s): Jiang Shuhao, Cui Shengliang, Song Haoran, Lu Yizi, Zhang Yong
Primary Institution: School of Information Engineering, Tianjin University of Commerce, Tianjin, China
Hypothesis
The integration of the Hyperbolic Sine–Cosine optimizer with the Nutcracker Optimization Algorithm will enhance UAV path planning efficiency.
Conclusion
The ISCHNOA algorithm outperforms traditional algorithms in UAV path planning, achieving lower costs and improved safety.
Supporting Evidence
- The ISCHNOA algorithm demonstrated superior performance in various UAV path planning scenarios.
- Experimental results showed that ISCHNOA can quickly identify near-optimal paths while reducing flight costs.
- The algorithm effectively avoids local optima, enhancing its applicability in complex environments.
Takeaway
This study shows a new way to help drones find the best paths to fly safely and quickly, especially in tricky places with obstacles.
Methodology
The study tested the ISCHNOA algorithm using 14 benchmark test functions and applied it to UAV path planning models.
Limitations
The performance of the ISCHNOA algorithm is less remarkable on high-dimensional problems.
Digital Object Identifier (DOI)
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