Servicios Personalizados
Revista
Articulo
Indicadores
- Citado por SciELO
- Accesos
Links relacionados
- Citado por Google
- Similares en SciELO
- Similares en Google
Compartir
DYNA
versión impresa ISSN 0012-7353
Resumen
MORENO-ESPINO, Mailyn y ROSETE-SUAREZ, Alejandro. Proactive local search based on FDC. Dyna rev.fac.nac.minas [online]. 2014, vol.81, n.184, pp.201-208. ISSN 0012-7353. https://doi.org/10.15446/dyna.v81n184.37303.
This paper introduces a proactive version of Hill Climbing (or Local Search). It is based on the identification of the best neighborhood through the repeated application of mutations and the evaluation of theses neighborhood by using FDC (Fitness Distance Correlation). The best neighborhood is used during a time window, and then the analysis is repeated. An experimental study was conducted in 28 functions on binary strings. The proposed algorithm achieves good performance compared to other metaheuristics (Evolutionary Algorithms, Great Deluge Algorithm, Threshold Accepting, and RRT).
Palabras clave : Metaheuristics; Agents; Proactive Behavior; Variable Neighborhood Search; FDC.