Hello, with this mail I want to point to my work done during this year's SoC: "Implementing a state of the art mincut/maxflow algorithm". Mentored by Douglas Gregor I implemented a maxflow/mincut algorithm for BGL which was originally presented by Vladimir Kolmogorov[1]. The documentation and description of the implementation can be found at: http://mp-vipa5.informatik.uni-mannheim.de/~diederich/data/soc/doc/kolmogoro... The goal of the project was to have an algorithm with a runtime which is comparable to other standard maxflow/mincut implementations. Performance measurements (http://stephan.diederich.googlepages.com/soc2006222) show that this goal was reached. What can be read from those charts is, that the runtime of the algorithms clearly depends on the underlying problem type. For graphs found in image segmentation problems and random graphs, the newly developed algorithm outperforms the existing alternative(s). Future work: In an extra version (kolmogogorv_max_flow_no_terminals.hpp) I changed the algorithm to omit all vertex-terminal edges. This is very interesting for graphs where many vertices are connected to the terminals. Instead of having those edges present in the graph, these capacities are stored directly as properties of the vertices. This gives a nice performance boost. The goal is to merge those two implementations into one. Full repository can be checked out from https://www.boost-consulting.com:8443/svn/main/boost/soc/2006/mincut-maxflow... and browsed via https://www.boost-consulting.com:8443/trac/soc/browser/boost/soc/2006/mincut... Algorithm's implementation only from: https://www.boost-consulting.com:8443/svn/main/boost/soc/2006/mincut-maxflow... As this is my very first contribution to Boost I would like to get as much feedback as possible. The learning curve is the steepest in the beginning... ;) Thanks a lot, Stephan [1] http://www.adastral.ucl.ac.uk/~vladkolm/papers/PHD.html