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.
| Original language | English |
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| Pages (from-to) | 61-73 |
| Number of pages | 13 |
| Journal | Genetic Programming and Evolvable Machines |
| Volume | 2 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 1 Jan 2001 |