An Ameliorated Harmony Search Algorithm With Hybrid Convergence Mechanism

The metaheuristic optimization algorithm Harmony search (HS), which imitates the process of music improvisation, is becoming widely used due to its simplicity and easy operation. However, basic HS has shortcomings low accuracy risk falling into local optimum. To overcome these problems, this article develops an ameliorated harmony with hybrid convergence mechanism, namely AHS-HCM. For new method, so-called mechanism mainly includes two important schemes. first scheme introduce a coefficient in improvisation further adjust performance, can improve final accuracy. second put forward non-linear domain for global exploration, it also helps efficiency. Besides, operation variables generation modified enrich behavior contribute find Fifteen typical CEC's benchmark functions are selected experiments, results clearly proved effectiveness It shown that, most cases, proposed AHS-HCM superior other variants as well some similar famous population-based algorithms terms stability.