Enhancing three variants of harmony search algorithm for continuous optimization problems

نویسندگان

چکیده

Meta-heuristic algorithms are well-known optimization methods, for solving real-world problems. Harmony search (HS) is a recognized meta-heuristic algorithm with an efficient exploration process. But the HS has slow convergence rate, which causes to have weak exploitation process in finding global optima. Different variants of introduced literature enhance and fix its problems, but most cases, still rate. Meanwhile, opposition-based learning (OBL), effective technique used improve performance different algorithms, including HS. In this work, we adopted new improved version OBL, three Search, by increasing rate speed these improving overall performance. The OBL named (IOBL), it from original adopting randomness increase solution's diversity. To evaluate hybrid run on benchmark functions compare obtained results versions. show that more compared versions A graph also algorithms.

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ژورنال

عنوان ژورنال: International Journal of Power Electronics and Drive Systems

سال: 2021

ISSN: ['2722-2578', '2722-256X']

DOI: https://doi.org/10.11591/ijece.v11i3.pp2343-2349