Paper Info
Title
Using landscape measures for the online tuning of heterogeneous distributed gas
Abstract
Tuning distributed genetic algorithms (dGAs) increases even more the task of finding an appropriate parameterization, since the migration operator adds, at least, five additional values that have to be set up. This work is a preliminary approach on using a landscape measure (the Fitness Distance Correlation) to dynamically adjust one of these five parameters, in particular, the migration period. The results have shown that, by using this information, the quality of the solutions is competitive with those obtained by the algorithms with the pre-tuned migration period, but with a saving of more than 100 hours of preliminary experimentation.
Year
DOI
Venue
2011
10.1145/2001858.2002070
GECCO (Companion)
Keywords
Field
DocType
fitness distance correlation,pre-tuned migration period,genetic algorithm,landscape measure,migration operator,preliminary experimentation,migration period,additional value,preliminary approach,online tuning,appropriate parameterization,tuning
Mathematical optimization,Additional values,Parametrization,Computer science,Distance correlation,Operator (computer programming),Artificial intelligence,Machine learning,Genetic algorithm
Conference
Citations 
PageRank 
References 
2
0.42
12
Authors
3
Name
Order
Citations
PageRank
Carolina Salto1357.61
Enrique Alba23796242.34
Francisco Luna314412.40