Harmony Search with Dynamic Adaptation of Parameters for the Optimization of a Benchmark Set of Functions

In this paper a fuzzy search algorithm harmony (FHS) is presented. The main difference between previous work is that this method uses a fuzzy system for dynamic parameter adaptation of the two main parameters throughout the iterations of the algorithm, which are: harmony memory accepting (HMR) and pitch adjustment (PArate), with the rules of the fuzzy system control the intensification and diversification of the search space is achieved. This method was applied to the mathematical functions provided by the CEC 2017, which are unimodal, multimodal, hybrid and composite functions to verify the efficiency of the proposed method. A comparison is presented to verify the results obtained with the original harmony search algorithm and the fuzzy harmony search algorithm.

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