Introduction In today’s supply chain systems wrought with competition, minimal costs and efficient delivery and inventory replenishments should characterize any supply chain system. The proposed system is a multi-echelon multi-period inventory model with the objective of minimizing the overall supply chain cost. In this model, the supply chain is typically defined by a number of network nodes linked together and characteristically defined by a dynamic supply and demand relationship covering a wide geographic location. The dynamism of the supply chain is characterized by varying inventory levels with time at each node. Here, orders are generated in the most downstream echelon with supply being replenished externally in the most upstream echelon. The main problem is to control the inventory level by optimizing the objective functions in relation to the number of orders in a given period of time. In this case, a robust multi-echelon model provides the most optimal solution to the problem. The rationale of a multi-echelon multi-period inventory system is cost effectiveness, efficiency, and reliability to optimize on the use of nodes. The Problem Description The three variables, what should be ordered, the quantity to be ordered, and order period, at each node critically influence the efficiency of a supply chain in a multi-echelon, multi-period, and multi-location or geographically dispersed inventory system (Love, 22). Different nodes play different roles in different supply chains. A comparative analysis of different supply chains reveals several options may be supplied upstream by one or several nodes, or where a series of nodes are supplied upstream and downstream (34) and (Sterman, 55). Typically, in the latter, the series consists of a last node which is subjected to external demand and external supply. The latter is a description of a typical serial chain. Whitin argues that a network design that optimizes inventory in the current supply chain environment to optimize supply by determining in real time the strategic location and specific inventory levels and requirements in the supply chain is a viable solution (45). However, Cachon, Taylor, and Schmidt argue that multi-echelon multi-period suffer from typical problems such as the degree of uncertainty in customer demands which is strongly correlated with specific methods of determining an accurate size of orders for every echelon in the supply chain for a given period to benefit from an optimum objective function (34) and (Simchi-Levi, Kaminski & Simchi-Levi, 34). Therefore, uncertainty, time, demand process, and geographic distributions determine to a large extent the optimality and minimization of inventory cost (Cachon and Lariviere, 56). Overly, these are typical control problems that demand due attention and techniques to solve them to optimize the whole supply chain system (Ben-Tal, Boyd, Nemirovski, 35) and (Sterman, 21). Problem statement A network of nodes or echelons are geographically distributed in a potential supply chain whose set of supply points are defined as i ∈ I with distribution sites defined by j ∈ J. Suppose the geographic zones for distribution in the supply chain a