Study on Test Generation of Sequential Circuits Based on Particle Swarm Optimization and Ant Algorithm

This paper presents a new method of automatic test generation for sequential circuits based on particle swarm optimization and ant algorithms. The hybrid algorithm utilizes characteristics of ant algorithm such as positive feedback and keeps basic characteristic of particle swarm optimization to guide the search further. Experiments based on the hybrid algorithm model are implemented. It can achieve higher fault coverages when compared with the results based on particle swarm optimization, yet execute time of test generation for both of them is nearly identical, and more compact test sets are achieved when compared with the results based on ant algorithm.