A Primary Study on Hyper-Heuristics to Customise Metaheuristics for Continuous optimisation

摘要: Literature is prolific with metaheuristics for solving continuous optimisation problems. But, in practice, it difficult to choose one appropriately. Moreover, necessary determine a good enough set of parameters the selected approach. Hence, this work proposes strategy based on hyper-heuristic tailoring population-based metaheuristics. Besides, our approach considers search operators from well-known techniques as building blocks new ones. We test through four benchmark functions and by varying their dimensions. obtain diverse configurations. observe possible performance boost when two or more are considered. This could be due previously unexplored interactions between such operators.