Decision Making Simulator for Supply Allocation Under Uncertainty This work presents a simulationbased testbed for evaluation of supply distribution strategies in a single product multiperiod twostage social welfare supply chain with a divergent network configuration of  n  supply points and  m  demand points. Further, the supply and demand per period are assumed to be uncertain, which necessitates the use of simulation. The testbed is demonstrated through a test scenario, which in turn is based on an existing supply network. In the demonstration, specific identified strategies were used to allocate the available supply among the demand points. Each of these strategies was individually used and simulated over a year and performance measures indicate how one strategy cannot be used for a prolonged period. Future work would consist of an automation element in the testbed for decision making in supply allocation.

Simulation of Allocation Policies for a Serial Inventory System under Advance Demand Information In this paper, we simulate allocation policies for a twostage inventory system that receives perfect advance demand information (ADI) from customers belonging to different demand classes. Demands for each customer class are generated by independent Poisson processes while the processing times are deterministic. All customers in the same class have the same demand lead time (the difference between the due date and the requested date) and backordering costs. Each stage in the inventory system follows orderbasestockpolicies where the replenishment order is issued upon arrival of a customer order. The problem requires a fast and reliable method that determines the system performance under different policies and ADI. Thus, we employ discreteevent simulation to obtain output parameters such as inventory costs, fill rates, waiting time, and order allocation times. A numerical analysis is conducted to identify a reasonable policy to use in this type of system.