A learning mechanism for adaptive fitness function in auto 3D graphics layout using genetic algorithm

In computer-aided drafting and designing area, interactive graphics are used for designing components, systems, layouts, and structures. There are currently several approaches using for automated graphical layout tools in designing the graphic. Our research aims to reduce design-working time, to learn user preferences, and to generate 3D graphical layout design automatically. An attempt to enable computers to generate 3D graphical layout design and presentation automatically by using the genetic algorithm (GA) has been discussed for a decade. An effective use of GA in automated graphical layout design relies on how closely it is possible to define a fitness function that can reflect the user preferences. In this paper, we introduce methods to define chromosome structures and fitness functions of the selected objects. A learning mechanism is employed to adjust the fitness values of the objects in the selected layout chosen by the users. By this approach, the fitness functions can be changed adaptively reflecting the selection and user preferences