Fuzzy Hyperheuristic Framework for GA Parameters Tuning

Author

Gudino-Penaloza, Fernando ; Gonzalez-Mendoza, Miguel ; Mora-Vargas, Jaime ; Hernandez-Gress, Neil

Author_Institution

CEM, Intell. Syst. Res. Group, ITESM, Atizapan de Zaragoza, Mexico

fYear

2013

fDate

24-30 Nov. 2013

Firstpage

53

Lastpage

58

Abstract

A fuzzy based hyperheuristic system is used for Genetic Algorithm self adaption. A fuzzy Takagi-Sugeno Inference System is used as High level Heuristic and the GA is used as Low-level heuristic. The framework allows to the system to automatically adjust their own parameters without the need for manual adjustment. The fuzzy system to handle uncertainty about which or in what proportion should adjust the parameters.

Keywords

fuzzy reasoning; genetic algorithms; heuristic programming; uncertainty handling; GA parameters tuning; automatic parameters adjustment; fuzzy Takagi-Sugeno inference system; fuzzy hyperheuristic system; genetic algorithm; high level heuristic; low level heuristic; uncertainty handling; Fuzzy logic; Genetic algorithms; Genetics; Optimization; Pattern recognition; Sociology; Statistics; Self Adaptive GA; Parameters Tuning; Fuzzy System; Hyperheuristic Framework;

fLanguage

English

Publisher

ieee

Conference_Titel

Artificial Intelligence (MICAI), 2013 12th Mexican International Conference on

Conference_Location

Mexico City

Print_ISBN

978-1-4799-2604-6

Type

conf

DOI

10.1109/MICAI.2013.48

Filename

6714647