In today's competitive business environment, enterprises consider supply chain management (SCM) to be a key factor for achieving cost efficiency and better profitability. A hierarchy of decisions with important economic implications has to be made in SCM � strategic, tactical, operational, and ad hoc. However, as attested by the large body of research work in this area, SCM is not a straightforward task. Supply chains (SCs) span across continents, involve numerous entities with different interests, and contend with various uncertainties. The complex maze of the network results in complex dynamics, which in turn could lead to unforeseen domino effects. These motivate the development of simulation models of the SC, which could capture the behavior of the entities, their interactions, the resulting dynamics, and the various uncertainties. These models provide decision support for SCM by allowing the user to evaluate the impact of a particular decision on the SC performance, analyze different SC policies, identify the consequences of a disruption, and determine remedial actions, through simulation.