Date of Award
Doctor of Philosophy (PhD)
Department of Operational Sciences
John O. Miller, PhD.
This research develops a flexible agent-based modeling and simulation (ABMS) framework for supply chain risk management with significant enhancements to standard ABMS methods and supply chain risk modeling. Our framework starts with the use of software agents to gather and process input data for use in our simulation model. For our simulation model, we extend an existing mathematical framework for discrete event simulation (DES) to ABMS and then implement the concepts of variable resolution modeling from the DES domain to ABMS and provide further guidelines for aggregation and disaggregation of supply chain models. Existing supply chain risk management research focuses on consumable item supply chains. Since the Air Force supply chain contains many reparable items, we fill this gap with our risk metrics framework designed for reparable item supply chains, which have greater complexity than consumable item supply chains. We present new metrics, along with existing metrics, in a framework for reparable item supply chain risk management and discuss aggregation and disaggregation of metrics for use with our variable resolution modeling.
DTIC Accession Number
Harper, Tiffany J., "Agent Based Modeling and Simulation Framework for Supply Chain Risk Management" (2012). Theses and Dissertations. 1211.