Abstract
This paper proposes a novel method based on interval type-2 fuzzy logic for the adaptive harmony search algorithm. Based on a study carried out previously it is decided to use a second input that we will be called diversity, and this in order to obtain that so close or far they are the harmonies of the solution. The method is applied to 11 mathematical benchmark functions using 2 and 10 variables to test the proposed method and present a comparison with the original method and with harmony search using type-1 fuzzy logic. In previous works we used the type-1 and type-2 fuzzy logic to dynamically adjust the parameters of the algorithm, such as the number of improvisations or the iterations, but adjusting each parameter separately. In this case we use as a second input the diversity and as output the harmony memory accepting parameter to achieve a control of the exploration and exploitation of the search space. We can say that this is the difference between the previous works and this proposed method.
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Peraza, C., Valdez, F., Castillo, O. (2018). Improved Method Based on Type-2 Fuzzy Logic for the Adaptive Harmony Search Algorithm. In: Castillo, O., Melin, P., Kacprzyk, J. (eds) Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications. Studies in Computational Intelligence, vol 749. Springer, Cham. https://doi.org/10.1007/978-3-319-71008-2_3
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DOI: https://doi.org/10.1007/978-3-319-71008-2_3
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