Elitist selection schemes for genetic algorithm based printed circuit board inspection system
This paper presents the implementation of a number of elitist schemes for a low cost printed circuit board (PCB) inspection system. This strategy also aims to explore the role of tournament and roulette-wheel in improving the existing system when using a deterministic selection scheme. In this system, GA is used to detect rotation angle and displacement of PCB placed arbitrarily on a conveyor belt passing under the camera. Deterministic, tournament and roulette-wheel selection scheme have been compared in terms of maximum fitness, rate of accuracy and computation time. The finding shows that deterministic outperformed the other two schemes in all categories and still proves to be an ideal candidate for GA-based PCB inspection system. The modifications on population size and implementation of center block image matching technique also contributed to the improvement of computational time of the system.