Supply Networks have recently been cast as complex adaptive systems in which interrelated sets of autonomous suppliers, manufacturers, distributors, and retailers adjust their activities to improve resource flow. A typical supply network has a large number of interactions and interdependencies among multiple firms which themselves may be part of multiple other supply networks. Alongside this intricate inter-organizational network, constantly changing market behavior provides an endlessly shifting landscape that necessitates both a complex and an adaptive approach towards understanding Supply Networks. The CAS view of supply networks, instead of making tractable causal assumptions about the non-linearity in a supply network, shows how complex system outcomes and behaviors flow from several organizations' actions and their interconnections. The network self-organizes through a complicated interplay of evolving structure and changing functions related to the flow of money, material and information.

At the Systems and Decision Making group at Vanderbilt, we are studying the evolutionary nature of Supply Networks under the following broad themes:

1. Developing complexity based theory for Supply Networks
2. Modeling growth in supply network using Agent based discrete time discrete event simulations
3. Policy optimization using RBDO techniques in supply networks
4. Analyzing chaotic dynamics in Supply Networks using non-linear time series and computational mechanics approaches.

ACKNOWLEDGEMENTS

This study is supported by funds from the National Science Foundation through the Vanderbilt University IGERT program on Risk and Reliability Engineering and, in part, by an Idaho National Laboratory Fellowship.