Business process management (BPM) continues to play a significant role in today's highly globalized world. In order to detect and prevent the gap between reference process model and the actual operation, process mining techniques discover operational model on the basis of the process logs. An important issue at BPM is to measure the similarity between the reference process model and discovered process model so that it can be possible to pinpoint where process participants deviate from the intended process description. In this paper, a hybrid quantitative approach is presented to measure the similarity between the process models. The proposed similarity metric is based on a hybrid process mining technique that makes use of genetic algorithms. The proposed approach itself is also a hybrid model that considers process activity dependencies and process structure.