Genetic algorithm for multi-objective experimental optimization

被引：2
|
作者：
Hannes Link
Dirk Weuster-Botz
机构：
[1] Technische Universität München,Lehrstuhl für Bioverfahrenstechnik
来源：
Bioprocess and Biosystems Engineering | 2006年 / 29卷
关键词：
Experimental design; Genetic algorithm; Multi-objective optimization; Software tool;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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).
引用
收藏
页码：385 / 390
页数：5
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