A Comparative Study of Ant Colony Optimization and Reactive Search for Graph Matching Problems

Many applications involve matching two graphs in order to identify their common features and compute their similarity. In this paper, we address the problem of computing a graph similarity measure based on a multivalent graph matching and which is generic in the sense that other well known graph similarity measures can be viewed as special cases of it. We propose and compare two different kinds of algorithms: an Ant Colony Optimization based algorithm and a Reactive Search. We compare the efficiency of these two algorithms on two different kinds of difficult graph matching problems and we show that they obtain complementary results.

• Type: Conference
• Year: 2006
• Where: EVOW
• Authors: Olfa Sammoud, Sébastien Sorlin, Christine Solnon, Khaled Ghédira
• Keywords: Artificial Intelligence, EVOW 2006, Graph Matching, Graph Similarity Measures, Multivalent Graph Matching