The rapid growth of program code is an important
problem in genetic programming systems. In the present
paper we investigate a selection scheme based on
multiobjective optimization. Since we want to obtain
accurate and small solutions, we reformulate this
problem as multiobjective optimization. We show that
selection based on the Pareto nondomination criterion
reduces code growth and processing time without
significant loss of solution accuracy.
%0 Journal Article
%1 ekart:2001:genp
%A Ekart, Aniko
%A Nemeth, S. Z.
%D 2001
%J Genetic Programming and Evolvable Machines
%K algorithms, code genetic growth, multiobjective optimization programming, scheme, selection
%N 1
%P 61--73
%R doi:10.1023/A:1010070616149
%T Selection Based on the Pareto Nondomination Criterion
for Controlling Code Growth in Genetic Programming
%V 2
%X The rapid growth of program code is an important
problem in genetic programming systems. In the present
paper we investigate a selection scheme based on
multiobjective optimization. Since we want to obtain
accurate and small solutions, we reformulate this
problem as multiobjective optimization. We show that
selection based on the Pareto nondomination criterion
reduces code growth and processing time without
significant loss of solution accuracy.
@article{ekart:2001:genp,
abstract = {The rapid growth of program code is an important
problem in genetic programming systems. In the present
paper we investigate a selection scheme based on
multiobjective optimization. Since we want to obtain
accurate and small solutions, we reformulate this
problem as multiobjective optimization. We show that
selection based on the Pareto nondomination criterion
reduces code growth and processing time without
significant loss of solution accuracy.},
added-at = {2008-06-19T17:35:00.000+0200},
author = {Ekart, Aniko and Nemeth, S. Z.},
biburl = {https://www.bibsonomy.org/bibtex/29b0224423b7b92f012a821d2cde4c047/brazovayeye},
doi = {doi:10.1023/A:1010070616149},
interhash = {4b9a4a4d8ecf81c48598ccb6eb115757},
intrahash = {9b0224423b7b92f012a821d2cde4c047},
issn = {1389-2576},
journal = {Genetic Programming and Evolvable Machines},
keywords = {algorithms, code genetic growth, multiobjective optimization programming, scheme, selection},
month = {March},
notes = {Article ID: 319813},
number = 1,
pages = {61--73},
timestamp = {2008-06-19T17:39:11.000+0200},
title = {Selection Based on the Pareto Nondomination Criterion
for Controlling Code Growth in Genetic Programming},
volume = 2,
year = 2001
}