The increase of digital circuit integrity and complexity has made fault diagnosis of circuits more and more difficult.The scale of test set has become very large because of redundancy

which costs lots of time and memory unnecessarily.It is important to acquire optimal test set for test application.Test set optimization

which can eliminate the redundancy

is one of key problems in fault diagnosis of digital circuits.Ant colony optimization

a new kind of random optimization algorithm

has become a better alternative to genetic algorithm in some areas.That algorithm has such advantages as less parameters and simple operations

so it is easier to be adopted.We propose a method based on ant colony optimization that solves test set optimization better than classic algorithm or genetic algorithm.The better performance of the proposed method is demonstrated by experimental results.