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GECCO
2008
Springer

Application domain study of evolutionary algorithms in optimization problems

11 years 2 months ago
Application domain study of evolutionary algorithms in optimization problems
This paper deals with the problem of comparing and testing evolutionary algorithms, that is, the benchmarking problem, from an analysis point of view. A practical study of the application domain of four representative evolutionary algorithms is carried out using a relevant set of real-parameter function optimization benchmarks. The four selected algorithms are the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) and the Differential Evolution (DE), due to their successful results in recent studies, a Genetic Algorithm with real parameter operators, used here as a reference approach because it is probably the most familiar to researchers, and the Macroevolutionary algorithm (MA), which is not widely known but it shows a very remarkable behavior in some problems. The algorithms have been compared running several tests over the benchmark function set to analyze their capabilities from a practical point of view, in other words, in terms of their usability. The characterization of ...
Pilar Caamaño, Francisco Bellas, José
Added 09 Nov 2010
Updated 09 Nov 2010
Type Conference
Year 2008
Where GECCO
Authors Pilar Caamaño, Francisco Bellas, José Antonio Becerra, Richard J. Duro
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