Paper Info
Title
An adjustment model in a geometric constraint solving problem
Abstract
An interesting problem related to geometric constraint solving is the choice of the "good" solution. The suitability and effectiveness of genetic algorithms applied to this problem has been demonstrated but their performance depends on the values assigned to their control parameters. Although there are recommendations in the specialised technical literature about values for these parameters, their optimal settings depend on the problem at hand. Therefore it would be interesting to define a model that automatically adjusts the values of the evolutive parameters as a function of the geometric problem.This paper proposes a meta-model that generates the recommendations for the right parameter values in genetic algorithms operating as a selector mechanism in constructive geometric constraint solvers. It should be stressed that the proposed model is general and automatic. This means that it is applicable to any context and works without the need for any user supervision.
Year
DOI
Venue
2006
10.1145/1141277.1141508
SAC
Keywords
Field
DocType
interesting problem,geometric problem,genetic algorithm,control parameter,geometric constraint,evolutive parameter,optimal setting,constructive geometric constraint solvers,adjustment model,right parameter value,bayesian networks,genetic algorithms,meta model,bayesian network
Mathematical optimization,Constructive,Computer science,Geometric networks,Bayesian network,Artificial intelligence,Geometric programming,Genetic algorithm
Conference
ISBN
Citations 
PageRank 
1-59593-108-2
0
0.34
References 
Authors
8
3
Name
Order
Citations
PageRank
Reyes Pavón1578.08
F. Díaz223112.75
M. Victoria Luzón3365.40