Metric-topological-evolutionary optimization

摘要: This article shows a novel approach for optimization and inverse problems based on evolutionary computation with the aim to satisfy two opposite requirements: exploration convergence. The proposed is particularly suitable parallel computing it gives its best both multimodal in which bad initializations can occur. algorithm has been called MeTEO point out metric-topological inspiration. In fact, hybridization of heuristics coming from swarm intelligence: flock-of-starlings (FSO; high capability but lack convergence), standard particle (which less explorative than FSO good convergence capability) third heuristic: bacterial chemotaxis (that no collective behaviour, skill capability). Finally, speeding up algorithm, technique t...