A new variant of the hybrid metaheutic MPCAHJ (Multi-Particle Collision Algorithm with Hooke-Jeeves method) is presented. Multi-Particle Collision Algorithm is a metaheuristic algorithm that performs a search on the search space. With the addition of the Rotation-Based Learning mechanism to the exploration search, a maior area of the search space has chance to be visited. The Hooke-Jeeves direct search method exploites the best solution found, allowing to achieve better solutions. The performance of all implementation are evaluated over twenty-two well known benchmark functions.
Comparación de diferentes algoritmos metaheurísticos en la estimación de parámetros del modelo relacional general de cromatografía líquida en columna Comparison between different metaheuristic algorithms in parameter estimation of the general relational model of column liquid chromatography
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