Palabras clave
Scatter Search
Nonlinear Optimization
Búsqueda Tabú
Búsqueda Dispersa
Optimización No Lineal
Cómo citar
Resumen
El artículo presenta una adaptación del algoritmo de Búsqueda Dispersa Multiobjetivo para la solucionar problemas de optimización vectorial no lineales continuos, empleando un enfoque de Búsqueda Tabú como un método generador de soluciones diversas. Memoria de Frequencias y otros mecanismos de escapes son utilizados para diversificar la búsqueda. La relación Pareto es aplicada para designar un subconjunto de las mejores soluciones generadas a ser soluciones de referencias. Una función de selección denominada selección de Kramer se utiliza para dividir al conjunto de referencia en dos subconjuntos. La distancia Euclideana es usada como una medida de disimilaridad a modo de hallar soluciones diversas que complementen los subconjuntos de soluciones potencialmente Pareto de alta calidad a ser combinadas. Como método de conbinación usamos la combinación convexa. El desempeño de este enfoque es evaluado con diferentes problemas de pruebas tomados de la literatura.
Citas
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