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

Abstract

In computer-aided drafting and designing area, interactive graphics are used for designing components, systems, layouts, and structures. There are several approaches using for automated graphical layout tools in designing the graphic currently. Our research work 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 Genetic Algorithm (GA) has been discussed for a decade. An effective use of GA in automated graphical layout design relies on how close to define a fitness function that can be reflected the user preferences. In this paper, we introduce the methods to define chromosome structures and fitness functions and of the selected objects. A learning mechanism is employed to adjust the fitness values of the objects in the selected layout choosing by the users. By this approach, the fitness functions can be changed adaptively reflecting the selection and user preferences.