Parameter tuning of metaheuristics using metaheuristics

Broderick Crawford, Claudio Valenzuela, Ricardo Soto, Eric Monfroy, Fernando Paredes

Resultado de la investigación: Contribución a una revistaArtículorevisión exhaustiva

8 Citas (Scopus)

Resumen

Using metaheuristics requires a lot of work setting different parameters. This paper presents a multilevel algorithm to tackle this issue. An upper level metaheuristic is used to determine the most appropriate set of parameters for a low level metaheuristic. This schema is applied to instances of Ant Colony System and Scatter Search metaheuristics that were designed to solve the Set Covering Problem. These algorithms had been widely used on the resolution of different optimization problems requiring an important effort on parameter setting. Here, we use a Genetic Algorithm to optimize the parameter values of Ant Colony System and Scatter Search solving the problem at hand. The idea is transferring the parameter setting effort of one algorithm to other algorithm. A multilevel approach is proposed so that one metaheuristic (Ant Colony or Scatter Search) acts as a low level metaheuristic whose parameters are tuned by a upper level metaheuristic (Genetic Algorithm).

Idioma originalInglés
Páginas (desde-hasta)3556-3559
Número de páginas4
PublicaciónAdvanced Science Letters
Volumen19
N.º12
DOI
EstadoPublicada - dic 2013
Publicado de forma externa

Huella

Profundice en los temas de investigación de 'Parameter tuning of metaheuristics using metaheuristics'. En conjunto forman una huella única.

Citar esto