Selection Based on the Pareto Nondomination Criterion for Controlling Code Growth in Genetic Programming

被引：47

作者：

Anikó Ekárt

S. Z. Németh

机构：

[1] Hungarian Academy of Sciences,Computer and Automation Research Institute

[2] Hungarian Academy of Sciences,Computer and Automation Research Institute

来源：

Genetic Programming and Evolvable Machines | 2001年 / 2卷 / 1期

关键词：

genetic programming; code growth; selection scheme; multiobjective optimization;

D O I：

10.1023/A:1010070616149

中图分类号：

学科分类号：

摘要：

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.

引用

页码：61 / 73

页数：12

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