Elitist generational genetic chromodynamics - a new radii-based evolutionary algorithm for multimodal optimization

摘要: A new radii-based evolutionary algorithm (EA) designed for multimodal optimization problems is proposed. The approach can be placed within the genetic chromodynamics framework and related to other EAs with local interaction, e.g. using species formation or clearing procedures. underlying motivation modifying original was preserve its ability search many optima in parallel while increasing convergence speed, especially complex problems, through generational selection different replacement schemes. applied function classification; obtained experimental results, part improved immensely by state-of-the-art parameter tuning (SPO), encouraged further investigation.