International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 87 - Number 19 |
Year of Publication: 2014 |
Authors: Amir Mosavi |
10.5120/15460-4057 |
Amir Mosavi . Decision-Making in Complicated Geometrical Problems. International Journal of Computer Applications. 87, 19 ( February 2014), 22-25. DOI=10.5120/15460-4057
Due to increasing the number of decision-making criteria in today's ever complicated geometrical optimization problems, the traditional multiobjective optimization approaches, whether a priori, a posteriori or interactive's, found to be insufficient and ineffective. In this paper the drawbacks of the current algorithms are reviewed and the urgent need for inserting a learning component in the optimization loop is discussed. In the following the methodology of reactive optimization for evolutionary interactive multiobjective optimization for solving complicated geometrical decision-making problems is adopted. The proposed brain-computer optimization follows to the paradigm of learning while optimizing, through the use of online machine learning techniques as an integral part of a self-tuning optimization scheme. At the end the effectiveness of the approach to geometrical problems is emphasized by providing the study case of optimal design problem of curves and surfaces.