利用模糊逻辑优化遗传算法的性能

Proceedings of IEEE International Conference on Intelligent Engineering Systems Pub Date : 1997-09-15 DOI:10.1109/INES.1997.632429

S. McClintock, T. Lunney, A. Hashim

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引用次数: 10

摘要

本文综述了遗传算法与模糊逻辑控制相结合的现有方法。提出了一种模糊逻辑控制遗传算法(FLC-GA)，该算法动态自动地进行算子选择和参数调整。模糊逻辑控制器通过使用关联的规则库和推理引擎来实现这种自动控制。这将使用遗传算法的反馈来决定采取何种控制行动以及何时采取行动，并在合理的时间限制内提供最佳解决方案。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Using fuzzy logic to optimize genetic algorithm performance

This paper reviews current methods of integrating genetic algorithms with fuzzy logic control. A fuzzy logic controlled genetic algorithm (FLC-GA) is proposed where operator selection and parameter adjustment is carried out dynamically and automatically. The fuzzy logic controller facilitates this automated control by employing an associated rule base and inference engine. This decides, using feedback from the genetic algorithm, what control action to take and when to take it, providing optimal solutions within reasonable time limitations.

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Proceedings of IEEE International Conference on Intelligent Engineering Systems

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