Automated design of part feeders using a genetic algorithm

We describe a genetic algorithm approach to the automated design of vibratory bowl part feeders. Our approach gives us near-optimal designs in much less time than previously published optimal, brute-force search methods. We have implemented our approach in an automated part feeder design system, and we present preliminary results generated by our system.