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About this paper
Yisheng Yang, Sim Kuan Goh, Qing Cai, Shen Yuong Wong, Ho-Kin Tang
Researchers at Xiamen University, Malaysia, developed the Yi optimization (YI) algorithm, a meta-heuristic inspired by the Yi Jing philosophy, unifying the Yin-Yang pair into a single "Yi-point" for balanced exploration and exploitation. The algorithm demonstrated superior or competitive performance against various optimizers on the IEEE CEC 2017 benchmarks, particularly improving effectiveness in higher-dimensional problems while maintaining low computational complexity.
Key insights
- Abstract philosophical concepts from traditions like the Yi Jing can be effectively translated into competitive and efficient meta-heuristic optimization algorithms.
- A single, dynamically updated "Yi-point" integrated with Cauchy flight and a decreasing archive duration can intrinsically manage the exploration-exploitation trade-off.
- The YI algorithm's design leads to robust and stable convergence behavior, making it suitable for complex, higher-dimensional optimization problems while maintaining low computational and space complexity.
Summary by alphaXiv.
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