根系生长实现全局优化

2015 IEEE International Conference on Information and Automation Pub Date : 2015-10-01 DOI:10.1109/ICINFA.2015.7279634

Hanning Chen, Xiaodan Liang, Weitao Yuan, Liling Sun, Maowei He, Nuo Ji

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引用次数: 0

摘要

本文提出了一种新的仿生优化器，即根系生长算法(RSGA)，该算法利用根系的觅食、记忆和通讯以及生长素调控机制。在对基准函数进行测试时，RSGA在精度、鲁棒性和收敛速度方面明显优于CMA-ES、PSO、GA和DE算法。

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Root system growth for global optimization

This paper proposed a novel bio-inspired optimizer, namely the root system growth algorithm (RSGA), which adopts the root foraging, memory and communication, and auxin-regulated mechanisms of the root system. When tested against benchmark functions, the RSGA markedly outperforms the CMA-ES, PSO, GA, and DE algorithms in terms of accuracy, robustness and convergence speed.

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2015 IEEE International Conference on Information and Automation

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