Nowadays the use of fuzzy logic has been increasing in popularity, and this is mainly due to the inference mechanism that allows simulating human reasoning in knowledge-based systems. The main contribution of this work is using the concepts of fuzzy logic in a method for dynamically adapting the main parameters of the harmony search algorithm during execution. Dynamical adaptation of parameters in metaheuristics has been shown to improve performance and accuracy in a wide range of applications. For this reason, we propose and approach for fuzzy adaptation of parameters in harmony search. Two case studies are considered for testing the proposed approach, the optimization of mathematical functions, which are unimodal, multimodal, hybrid, and composite functions and a control problem without noise and when noise is considered. A statistical comparison between the harmony search algorithm and the fuzzy harmony search algorithm is presented to verify the advantages of the proposed approach.

中文翻译：

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基准函数和模糊控制器协调搜索优化的动态参数自适应中的模糊逻辑

如今，模糊逻辑的使用日益普及，这主要是由于推理机制可以在基于知识的系统中模拟人类推理。这项工作的主要贡献是在执行过程中动态调整和声搜索算法的主要参数的方法中使用了模糊逻辑的概念。已经证明，元启发法中参数的动态适应可以提高广泛应用中的性能和准确性。由于这个原因，我们提出了和声搜索中参数的模糊自适应的方法。考虑了两个案例研究来测试所提出的方法，数学函数的优化（单峰函数，多峰函数，混合函数和复合函数）以及无噪声且考虑噪声时的控制问题。