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基于改进野马优化算法的AGV路径规划 - 中国知网
Source: kns.cnki.net
Article summary:
1. A new AGV (automated guided vehicle) path planning algorithm based on improved wild horse optimization is proposed.
2. The algorithm balances global exploration and local mining capabilities with a non-linear adaptive factor, increases the diversity of offspring individuals with an offset evolution strategy, and guides individuals to move towards the global optimal position with a golden sine segmentation coefficient.
3. Simulation experiments have verified that the improved wild horse optimization algorithm can reduce the length of AGV path planning by 5.84%.
Article analysis:
The article is generally reliable and trustworthy in its content, as it provides detailed information about the proposed AGV path planning algorithm based on improved wild horse optimization, including its components such as non-linear adaptive factor, offset evolution strategy, golden sine segmentation coefficient, and B-spline curve smoothing strategy. The article also provides evidence for its claims through simulation experiments which show that the improved wild horse optimization algorithm can reduce the length of AGV path planning by 5.84%.
However, there are some potential biases in the article which should be noted. For example, it does not explore any counterarguments or alternative solutions to the problem of AGV path planning. Additionally, it does not provide any information about possible risks associated with using this algorithm or how it could be further improved upon in future research. Furthermore, while it mentions funding sources for this research project at the end of the article, it does not provide any details about who funded this project or why they chose to fund it.