I have recently been doing some work on supply chains and, more generally, agent-based modeling in general. There is a certain art to making an agent-based model that is complex enough to capture the problem you are trying to model but still simple enough to remain manageable. Languages like NetLogo are excellent in that they eliminate nearly all extraneous code and one is left with something that almost (OK, maybe I'm being generous) looks like pseudo-code. Nearly all the code relates directly to the problem.

Still, its lots of fun.

On that note, I have posted a NetLogo model on supply chain survivability. The model itself is interesting in that I had to implement Dijistra's to calculate the minimal path between every pair of nodes. This was needed to later calculate the graph's clustering coefficient and the characteristic path length—two measures of a graph's connectivity, the smaller they are the closer everyone is to everyone else (thus, the shorter it takes to get items to the customers). Also note that the model generates small-world graphs (using preferential attachment) as well as random graphs. This model is the basis of some work we are doing. Anyone out there interested in this kind of stuff, let me know.