An introduction to NURBS: with historical perspective
An introduction to NURBS: with historical perspective
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Design exploration through bidirectional modeling of constraints
Design exploration through bidirectional modeling of constraints
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
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The use of computational methodologies for the optimization of aesthetic parameters is not frequent mainly due to the fact that these parameters are not quantifiable and are subjective. In this work an interactive methodology based on the use of multi-objective optimization algorithms is proposed. This strategy associates the results of different optimization runs considering the existent quantifiable objectives and different sets of boundary conditions concerning the decision variables, as defined by an expert decision maker. The associated results will serve as initial population of solutions for a final optimization run. The idea is that a more global picture of potential "good" solutions can be found. At the end this will facilitate the work of the expert decision maker since more solutions are available. The method was applied to a case study and the preliminary results obtained showed the potentially of the strategy adopted.