IGA-Based User Evaluation Driven Optimization Design of Forklift Styling

摘要

Considering the requirements for efficiency and precision in the forklift styling, the authors developed the forklift optimizing system for its styling based on the interactive genetic algorithms (IGA). The system includes parameter optimization, color optimization and part combination three modules. The parameter optimization module can find the user defined parameters of the forklift 3D models and generate new models. Color optimization module can group the model surfaces and render the groups with different color. New color plans are generated through random changing of the colors in each group. The parts combination module divides forklift into several parts and build lib for each part. The module can pick parts from the lib and assemble them into a whole forklift and demonstrate them. The thesis developed a protosystem on the Solidworks platform with VBA programming tools. Interactive genetic algorithms are applied to realize the three module's function.