In this paper, we develop a fingerprint matching method which operates by first introducing an integrated measure, which combines two different matching criteria based on heterogeneous features. We then devise a genetically guided algorithm to optimise the integrated measure for simultaneous fingerprint alignment and verification. The proposed method is evaluated through experiments conducted on two public domain collections of fingerprint images and compared with related work, with very encouraging results.