Genetic algorithm for multi-objective experimental optimization.
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).
Link
Hannes
H
Lehrstuhl für Bioverfahrenstechnik, Technische Universität München, Boltzmannstr. 15, Garching 85748, Germany.
Weuster-Botz
Dirk
D
D000465:Algorithms; D003198:Computer Simulation; D008954:Models, Biological; D011786:Quality Control; D012984:Software; D013598:Systems Theory