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harmony search algorithm: a variant with self-regulated fretwidth

APPLIED MATHEMATICS AND COMPUTATION 2015年 266卷 1127-1152页

作者： Amaya, Ivan Cruz, Jorge Correa, Rodrigo Univ Ind Santander Sch Elect Elect & Telecommun Engn Bucaramanga Colombia

This article presents a novel modification of the harmony search (HS) algorithm that is able to self-tune as the search progress. This adaptive behavior is independent of total iterations. Moreover, it requires less iterations and provides more precision than other variants of HS. Its effectiveness and performance was assessed, comparing our data against four well known and recent modifications of HS: IHS (Improved harmony search, 2007), ABHS (Adjustable Bandwidth harmony search, 2014), PAHS (Parameter Adaptive harmony search, 2014), and IGHS (Intelligent Global harmony search, 2014). Unlike other works, we did not analyze the data for a given number of iterations. Instead, we ran each algorithm until it achieved a given level of precision, and analyzed the number of iterations it required. Our test benchmark contained 30 standard test functions distributed like this: 11 unimodal, 8 multimodal with fixed dimensions, and 11 multimodal with variable dimensions. The latter also included a function whose optima was located at a different coordinate in each dimension. The search domain for each function was fixed according to the literature, though we also executed tests regarding the effect of varying it. We carried out a parameter sweep to find adequate values for each parameter of our proposed algorithm, analyzing 100 independent runs for 648 different combinations. Data confirm the implemented procedure outperformed the other variants for problems in 2D and in 5D. Scaling the test functions to 10D, 30D, and 50D reduced the convergence rate of the implemented procedure, but it still outperformed IHS, ABHS, and PAHS. In some cases (e.g. Schwefel function in 30D), the self-regulated fretwidth harmony search algorithm (SFHS) was found to be the fastest approach. It was also found that IGHS performs well for optimization problems whose optima is located at the same coordinates in all dimensions, but not as well in other scenarios. Our proposed algorithm (SFHS) is not hind

关键词： Global optimization harmony search algorithm Metaheuristic self-regulated fret width harmony search algorithm Standard test function

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