Title
Variable-Dimensional Optimization with Evolutionary Algorithms Using Fixed-Length Representations
Abstract
This paper discusses a simple representation of variable-d imensional optimization problems for evolutionary algorithms. Altho ugh it was successfully applied to the optimization of multi-layer optical coating s, it is shown that it intro- duces a unintentional bias into the search process with resp ect to the probability of a dimension being generated by mutation and recombination. In order to ex- amine the impact of the bias, the representation was applied to another variable- dimensional problem, the simultaneous estimation of model orders and model parameters of instances of autoregressive moving average processes (ARMA). The results of the parameter study show that quality of the es timation can be improved by removing the bias.
Year
DOI
Venue
1998
10.1007/BFb0040779
Evolutionary Programming
Keywords
Field
DocType
fixed-length representations,variable-dimensional optimization,optimization problem,evolutionary algorithm,optical coating,moving average process
Autoregressive–moving-average model,Mathematical optimization,Evolutionary algorithm,Computer science,Arma process,Estimation theory,Optimization problem,Genetic algorithm
Conference
ISBN
Citations 
PageRank 
3-540-64891-7
3
0.48
References 
Authors
4
2
Name
Order
Citations
PageRank
Joachim Sprave16910.21
Susanne Rolf2132.16