Abstract
A new software tool making use of a genetic algorithm for multi-objective experimental optimization (GAME.opt) was developed based on a strength Pareto evolutionary algorithm. The software deals with high dimensional variable spaces and unknown interactions of design variables. This approach was evaluated by means of multi-objective test problems replacing the experimental results. A default parameter setting is proposed enabling users without expert knowledge to minimize the experimental effort (small population sizes and few generations).
| Original language | English |
|---|---|
| Pages (from-to) | 385-390 |
| Number of pages | 6 |
| Journal | Bioprocess and Biosystems Engineering |
| Volume | 29 |
| Issue number | 5-6 |
| DOIs | |
| State | Published - Dec 2006 |
Keywords
- Experimental design
- Genetic algorithm
- Multi-objective optimization
- Software tool