Decision support and design evolution: Integrating genetic algorithms, CFD and visualization

This paper describes a decision support evolution model using Genetic Algorithm (GA) as the evolution algorithm and Computational Fluid Dynamics (CFD) as the evaluation mechanism. The model is integrated with a visualization module to allow users to interact and select form instances as the design evolves. The advantages of such an evolutionary decision support design approach is that diverse instances of the state space can be investigated in relation to specific goal requirements which will enhance the possibility of discovering a variety of potential solutions. The model allows the user to explore and visualize the design evolution and its form generation in an attempt to stimulate the designer creativity that might contribute to their output. The process uses an iterative approach that allows design to be evaluated using CFD analysis automatically to maximize several thermal and ventilation criteria. Design change will then be performed, remeshed and displayed based on the evolutionary algorithms. The process allows the user to experience the morphing of the design based on its performance and continues until the designer has the opportunity to visualize the evolution of the final set of design alternatives.