Fuzzy Harmony Search Algorithm Using an Interval Type-2 Fuzzy Logic Applied to Benchmark Mathematical Functions

This paper presents a fuzzy harmony search algorithm (FHS) based on an interval type-2 fuzzy logic system for dynamic parameter adaptation. The harmony memory accepting (HMR) and pitch adjustment (PArate) parameters are changing during the iterations in the improvisation process of this algorithm using the fuzzy system. The FHS has been successfully applied to various benchmark optimization problems. Numerical results reveal that the proposed algorithm can find better solutions when compared to a type-1 FHS and other heuristic methods and is a powerful search algorithm for various benchmark optimization problems.

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